{"title":"典型干旱区 PM2.5 和 O3 的时空变化及与土地利用的关系--景观模式分析","authors":"","doi":"10.1016/j.scs.2024.105689","DOIUrl":null,"url":null,"abstract":"<div><p>Land use – landscape pattern act as pollutant sources carries for PM<sub>2.5</sub> and ozone, understanding the relationship between them is valuable for the management of atmospheric environment. In this investigation, we examined the spatiotemporal distribution characteristics of PM<sub>2.5</sub> and ozone in Xinjiang during 2000 ∼ 2022. Meanwhile, we employed the random forest model under optimal model selection to explore the response of the land use - landscape pattern to the pollutants. The conclusions suggested: (1) PM<sub>2.5</sub> in 94.82% of the area showed a significant decrease, with high levels concentrated in the Tarim Basin, Turpan-Hami Basin. Ozone demonstrated a remarkable upward trend in 99.30% of the region, showing high levels in the Tarim Basin and the northern Xinjiang. (2) Upon comparison with the univariate and stepwise linear regression models, random forest model holds significant practical value in quantifying the impact of pollutants on land use-landscapes. (3) In the land use – landscape pattern, the complexity and aggregation of cropland and water, the degree of connectivity in barren and impervious, the diversity and complexity of forest, and the degree of aggregation of grasslands all strongly impact PM<sub>2.5</sub>. For ozone concentrations, the index characterizing the degree of patchy aggregation is overwhelmingly dominant.</p></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":null,"pages":null},"PeriodicalIF":10.5000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of spatiotemporal variation and relationship to land use – landscape pattern of PM2.5 and O3 in typical arid zone\",\"authors\":\"\",\"doi\":\"10.1016/j.scs.2024.105689\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Land use – landscape pattern act as pollutant sources carries for PM<sub>2.5</sub> and ozone, understanding the relationship between them is valuable for the management of atmospheric environment. In this investigation, we examined the spatiotemporal distribution characteristics of PM<sub>2.5</sub> and ozone in Xinjiang during 2000 ∼ 2022. Meanwhile, we employed the random forest model under optimal model selection to explore the response of the land use - landscape pattern to the pollutants. The conclusions suggested: (1) PM<sub>2.5</sub> in 94.82% of the area showed a significant decrease, with high levels concentrated in the Tarim Basin, Turpan-Hami Basin. Ozone demonstrated a remarkable upward trend in 99.30% of the region, showing high levels in the Tarim Basin and the northern Xinjiang. (2) Upon comparison with the univariate and stepwise linear regression models, random forest model holds significant practical value in quantifying the impact of pollutants on land use-landscapes. (3) In the land use – landscape pattern, the complexity and aggregation of cropland and water, the degree of connectivity in barren and impervious, the diversity and complexity of forest, and the degree of aggregation of grasslands all strongly impact PM<sub>2.5</sub>. For ozone concentrations, the index characterizing the degree of patchy aggregation is overwhelmingly dominant.</p></div>\",\"PeriodicalId\":48659,\"journal\":{\"name\":\"Sustainable Cities and Society\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":10.5000,\"publicationDate\":\"2024-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Cities and Society\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2210670724005146\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670724005146","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
Analysis of spatiotemporal variation and relationship to land use – landscape pattern of PM2.5 and O3 in typical arid zone
Land use – landscape pattern act as pollutant sources carries for PM2.5 and ozone, understanding the relationship between them is valuable for the management of atmospheric environment. In this investigation, we examined the spatiotemporal distribution characteristics of PM2.5 and ozone in Xinjiang during 2000 ∼ 2022. Meanwhile, we employed the random forest model under optimal model selection to explore the response of the land use - landscape pattern to the pollutants. The conclusions suggested: (1) PM2.5 in 94.82% of the area showed a significant decrease, with high levels concentrated in the Tarim Basin, Turpan-Hami Basin. Ozone demonstrated a remarkable upward trend in 99.30% of the region, showing high levels in the Tarim Basin and the northern Xinjiang. (2) Upon comparison with the univariate and stepwise linear regression models, random forest model holds significant practical value in quantifying the impact of pollutants on land use-landscapes. (3) In the land use – landscape pattern, the complexity and aggregation of cropland and water, the degree of connectivity in barren and impervious, the diversity and complexity of forest, and the degree of aggregation of grasslands all strongly impact PM2.5. For ozone concentrations, the index characterizing the degree of patchy aggregation is overwhelmingly dominant.
期刊介绍:
Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including:
1. Smart cities and resilient environments;
2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management;
3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management);
4. Energy efficient, low/zero carbon, and green buildings/communities;
5. Climate change mitigation and adaptation in urban environments;
6. Green infrastructure and BMPs;
7. Environmental Footprint accounting and management;
8. Urban agriculture and forestry;
9. ICT, smart grid and intelligent infrastructure;
10. Urban design/planning, regulations, legislation, certification, economics, and policy;
11. Social aspects, impacts and resiliency of cities;
12. Behavior monitoring, analysis and change within urban communities;
13. Health monitoring and improvement;
14. Nexus issues related to sustainable cities and societies;
15. Smart city governance;
16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society;
17. Big data, machine learning, and artificial intelligence applications and case studies;
18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems.
19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management;
20. Waste reduction and recycling;
21. Wastewater collection, treatment and recycling;
22. Smart, clean and healthy transportation systems and infrastructure;