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Long-term variations and formation drivers of PM2.5 nitrate in a megacity of Guanzhong Plain, China: Implications for air quality management.

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Title: Long-term variations and formation drivers of PM2.5 nitrate in a megacity of Guanzhong Plain, China: Implications for air quality management.
Authors: Wen, Liang1 (AUTHOR), Yang, Yan1 (AUTHOR), Zhang, Yujie1 (AUTHOR), Feng, Jiaying2 (AUTHOR), Gao, Rui1 (AUTHOR), Guo, Wei3 (AUTHOR), Guo, Shengnan3 (AUTHOR), Wang, Hao3 (AUTHOR), Chai, Fahe1 (AUTHOR), Herrmann, Hartmut4,5 (AUTHOR), Tilgner, Andreas4,6 (AUTHOR), Schaefer, Thomas4 (AUTHOR), Li, Hong1 (AUTHOR) lihong@craes.org.cn, Gao, Jian1 (AUTHOR) gaojian@craes.org.cn
Source: Journal of Environmental Sciences (Elsevier). Aug2026, Vol. 166, p581-590. 10p.
Subject Terms: *Air quality management, *Emission control, *Cities & towns, *Seasonal temperature variations, Particulate nitrate
Geographic Terms: Xi'an Shi (China), China
Abstract: • Nitrate (NO 3 -) was the largest component of PM 2.5 in Xi'an in 2023. • NO 3 - undergoes concentration inflection and raised fraction in PM 2.5 in 2003 – 2023. • Seasonal variations of NO 3 - formation drivers necessitated different control strategies. • Insufficient VOCs and NH 3 reductions limited NO x reduction effects on NO 3 - controls. The reduction in nitrate (NO 3 -) is crucial for further mitigating atmospheric PM 2.5 pollution. Guanzhong Plain is a significant region of PM 2.5 control in China. To reveal the variation characteristics and formation drivers of NO 3 - in this region, a comprehensive investigation had been conducted by combining field observations in the representative city namely Xi'an with MCM-CAPRAM multi-phase chemical box model. Over 2003–2023, NO 3 - concentrations showed an initial increase followed by a decline after inflection points, while its ratios to PM 2.5 and SO 4 2- persistently rose. Recent observations in 2023 presented the largest contributions of NO 3 - to PM 2.5 by 24.0 %, 17.9 %, 23.6 % and 20.9 % during four seasons, respectively. Case statistics and model simulations collectively indicated that NO 3 - formations exhibited positive sensitivity to O 3 concentrations and VOCs emissions during winter, and positive responses to NO 2 concentrations and NO x emissions in other seasons. Furthermore, NO 3 - formations were sensitive to particulate NH 4 + available for neutralizing HNO 3 and NH 3 emissions. The simulation results, based on various emission reduction scenarios, indicate the necessity of a coordinated multi-pollutant reduction scheme, which is subject to seasonal differentiation. Unlike the long-term air pollution controls in Beijing, a greater reduction in NO x emissions failed to achieve proportional decrease in NO 3 - concentration in Xi'an due to accelerated atmospheric oxidation intensity from an excessive emission reduction ratio of NO x to VOCs and insufficient decreases in NH 3 emissions. Overall, this study provides a scientific basis for formulating targeted nitrate control policies, offering global reference for PM 2.5 mitigation strategies. [Display omitted] [ABSTRACT FROM AUTHOR]
Copyright of Journal of Environmental Sciences (Elsevier) is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Long-term variations and formation drivers of PM2.5 nitrate in a megacity of Guanzhong Plain, China: Implications for air quality management.
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  Data: <searchLink fieldCode="AR" term="%22Wen%2C+Liang%22">Wen, Liang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yang%2C+Yan%22">Yang, Yan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Yujie%22">Zhang, Yujie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Feng%2C+Jiaying%22">Feng, Jiaying</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gao%2C+Rui%22">Gao, Rui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guo%2C+Wei%22">Guo, Wei</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Guo%2C+Shengnan%22">Guo, Shengnan</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Hao%22">Wang, Hao</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chai%2C+Fahe%22">Chai, Fahe</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Herrmann%2C+Hartmut%22">Herrmann, Hartmut</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tilgner%2C+Andreas%22">Tilgner, Andreas</searchLink><relatesTo>4,6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schaefer%2C+Thomas%22">Schaefer, Thomas</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Hong%22">Li, Hong</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> lihong@craes.org.cn</i><br /><searchLink fieldCode="AR" term="%22Gao%2C+Jian%22">Gao, Jian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> gaojian@craes.org.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Environmental+Sciences+%28Elsevier%29%22">Journal of Environmental Sciences (Elsevier)</searchLink>. Aug2026, Vol. 166, p581-590. 10p.
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  Data: *<searchLink fieldCode="DE" term="%22Air+quality+management%22">Air quality management</searchLink><br />*<searchLink fieldCode="DE" term="%22Emission+control%22">Emission control</searchLink><br />*<searchLink fieldCode="DE" term="%22Cities+%26+towns%22">Cities & towns</searchLink><br />*<searchLink fieldCode="DE" term="%22Seasonal+temperature+variations%22">Seasonal temperature variations</searchLink><br /><searchLink fieldCode="DE" term="%22Particulate+nitrate%22">Particulate nitrate</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Xi'an+Shi+%28China%29%22">Xi'an Shi (China)</searchLink><br /><searchLink fieldCode="DE" term="%22China%22">China</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: • Nitrate (NO 3 -) was the largest component of PM 2.5 in Xi'an in 2023. • NO 3 - undergoes concentration inflection and raised fraction in PM 2.5 in 2003 – 2023. • Seasonal variations of NO 3 - formation drivers necessitated different control strategies. • Insufficient VOCs and NH 3 reductions limited NO x reduction effects on NO 3 - controls. The reduction in nitrate (NO 3 -) is crucial for further mitigating atmospheric PM 2.5 pollution. Guanzhong Plain is a significant region of PM 2.5 control in China. To reveal the variation characteristics and formation drivers of NO 3 - in this region, a comprehensive investigation had been conducted by combining field observations in the representative city namely Xi'an with MCM-CAPRAM multi-phase chemical box model. Over 2003–2023, NO 3 - concentrations showed an initial increase followed by a decline after inflection points, while its ratios to PM 2.5 and SO 4 2- persistently rose. Recent observations in 2023 presented the largest contributions of NO 3 - to PM 2.5 by 24.0 %, 17.9 %, 23.6 % and 20.9 % during four seasons, respectively. Case statistics and model simulations collectively indicated that NO 3 - formations exhibited positive sensitivity to O 3 concentrations and VOCs emissions during winter, and positive responses to NO 2 concentrations and NO x emissions in other seasons. Furthermore, NO 3 - formations were sensitive to particulate NH 4 + available for neutralizing HNO 3 and NH 3 emissions. The simulation results, based on various emission reduction scenarios, indicate the necessity of a coordinated multi-pollutant reduction scheme, which is subject to seasonal differentiation. Unlike the long-term air pollution controls in Beijing, a greater reduction in NO x emissions failed to achieve proportional decrease in NO 3 - concentration in Xi'an due to accelerated atmospheric oxidation intensity from an excessive emission reduction ratio of NO x to VOCs and insufficient decreases in NH 3 emissions. Overall, this study provides a scientific basis for formulating targeted nitrate control policies, offering global reference for PM 2.5 mitigation strategies. [Display omitted] [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Environmental Sciences (Elsevier) is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.jes.2025.11.058
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        Text: English
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        PageCount: 10
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      – SubjectFull: Air quality management
        Type: general
      – SubjectFull: Emission control
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      – SubjectFull: Cities & towns
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      – SubjectFull: Seasonal temperature variations
        Type: general
      – SubjectFull: Particulate nitrate
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      – SubjectFull: Xi'an Shi (China)
        Type: general
      – SubjectFull: China
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      – TitleFull: Long-term variations and formation drivers of PM2.5 nitrate in a megacity of Guanzhong Plain, China: Implications for air quality management.
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              Text: Aug2026
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