Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/119201
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Civil and Environmental Engineering | en_US |
| dc.contributor | Research Institute for Land and Space | en_US |
| dc.creator | Li, Y | en_US |
| dc.creator | Wang, Y | en_US |
| dc.creator | He, Y | en_US |
| dc.creator | Cai, H | en_US |
| dc.creator | Wang, H | en_US |
| dc.creator | Yan, Z | en_US |
| dc.creator | Zhou, Z | en_US |
| dc.creator | Wu, G | en_US |
| dc.creator | Zhou, Y | en_US |
| dc.creator | Guo, H | en_US |
| dc.creator | Wang, B | en_US |
| dc.date.accessioned | 2026-06-09T05:38:48Z | - |
| dc.date.available | 2026-06-09T05:38:48Z | - |
| dc.identifier.issn | 1001-0742 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/119201 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.subject | Control strategy | en_US |
| dc.subject | Master chemical mechanism | en_US |
| dc.subject | Photochemical evolution | en_US |
| dc.subject | Photochemical trajectory model | en_US |
| dc.subject | Volatile organic compounds | en_US |
| dc.title | Photochemical formation process of ozone and spatiotemporally targeted control strategies along the transport pathways in the Pearl River Delta region | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 576 | en_US |
| dc.identifier.epage | 586 | en_US |
| dc.identifier.volume | 161 | en_US |
| dc.identifier.doi | 10.1016/j.jes.2025.05.032 | en_US |
| dcterms.abstract | Regional ozone (O<inf>3</inf>) pollution is currently a major challenge for urban agglomerations in China, including the Pearl River Delta (PRD) region. Understanding the cross-city photochemical evolution of O<inf>3</inf> is crucial for developing spatiotemporally targeted control strategies. In this study, three major transport pathways across cities in the PRD region were identified through multiyear airflow trajectory cluster analysis. A photochemical trajectory model (PTM) coupled with the near-explicit Master Chemical Mechanism (MCM) was employed to elucidate the photochemical processes along these pathways. The spatiotemporal variations in O<inf>3</inf> simulations indicated that intensive noontime O<inf>3</inf> production rates in upwind cities (e.g., Foshan and Guangzhou) substantially contributed to O<inf>3</inf> episodes in downwind ones along the north/northeastern transport pathways. Additionally, O<inf>3</inf> formation regimes shifted from volatile organic compounds (VOCs) regime to a transitional regime around midday, suggesting the effectiveness of time-resolved precursor controls, specifically, VOCs reduction during morning hours followed by coordinated nitrogen oxides (NO<inf>x</inf>) and VOCs reductions post-noon in the relevant cities. Furthermore, key VOC species and their sources (i.e., industrial processes and on-road mobile emissions) from responsible cities were traced and their downstream impacts were estimated. In the northern and northeastern cases, morning anthropogenic emissions from Foshan and Guangzhou accounted for 29 % and 42 % of O<inf>3</inf> concentrations in downwind Zhuhai and Jiangmen, respectively, implying the necessity of spatiotemporally targeted control strategies. This study enhances our understanding of inter-city O<inf>3</inf> photochemical evolution and provides actionable insights for spatiotemporally differentiated control strategies on regional O<inf>3</inf> mitigation. | en_US |
| dcterms.accessRights | embargoed access | en_US |
| dcterms.bibliographicCitation | Journal of environmental sciences, Mar. 2026, v. 161, p. 576-586 | en_US |
| dcterms.isPartOf | Journal of environmental sciences | en_US |
| dcterms.issued | 2026-03 | - |
| dc.identifier.scopus | 2-s2.0-105023498593 | - |
| dc.identifier.eissn | 1878-7320 | en_US |
| dc.description.validate | 202606 bchy | en_US |
| dc.description.oa | Not applicable | en_US |
| dc.identifier.SubFormID | G001807/2026-05 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | This work was supported by the National Key R&D Program of China (No. 2023YFC3709201 ), the National Natural Science Foundation of China (Nos. 42121004 and 42005080 ), the Science and Technology Project of Guangdong Province (No. 2024B1212040006 ), the Research Grants Council of the Government of the Hong Kong Special Administrative Region via General Research Fund Scheme (No. PolyU-152124/21E ), the research support scheme of Research Institute for Land and Space at the Hong Kong Polytechnic University (No. 1-CD79 ) and the Start-up Fund for RAPs under the Strategic Hiring Scheme of the Hong Kong Polytechnic University (No. 1-BD3T ). We are grateful to Guangdong Ecological Environmental Monitoring Center for the online VOC measurements. The authors thank Kevin Zou for constructive discussions on visualization. | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.date.embargo | 2028-03-31 | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
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