Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement

To better understand the changes in air pollutants in an industrial city, Handan, North China, during the COVID-19 lockdown period, the air quality and meteorological conditions were recorded from 1 January to 3 March 2020 and the corresponding period in 2019. Compared to the corresponding period in...

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Autores:
Niu, Hongya
Zhang, Chongchong
Hu, Wei
Hu, Tafeng
Wen, Chunmiao
Hu, Sihao
Silva Oliveira, Luis Felipe
Gao, Nana
bao, xiaolei
Fan, Jingsen
Tipo de recurso:
Article of investigation
Fecha de publicación:
2022
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/9626
Acceso en línea:
https://hdl.handle.net/11323/9626
https://repositorio.cuc.edu.co/
Palabra clave:
COVID-19 lockdown
Industrial city
Air quality
Potential source contribution function
Rights
openAccess
License
Atribución 4.0 Internacional (CC BY 4.0)
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oai_identifier_str oai:repositorio.cuc.edu.co:11323/9626
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement
title Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement
spellingShingle Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement
COVID-19 lockdown
Industrial city
Air quality
Potential source contribution function
title_short Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement
title_full Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement
title_fullStr Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement
title_full_unstemmed Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement
title_sort Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvement
dc.creator.fl_str_mv Niu, Hongya
Zhang, Chongchong
Hu, Wei
Hu, Tafeng
Wen, Chunmiao
Hu, Sihao
Silva Oliveira, Luis Felipe
Gao, Nana
bao, xiaolei
Fan, Jingsen
dc.contributor.author.none.fl_str_mv Niu, Hongya
Zhang, Chongchong
Hu, Wei
Hu, Tafeng
Wen, Chunmiao
Hu, Sihao
Silva Oliveira, Luis Felipe
Gao, Nana
bao, xiaolei
Fan, Jingsen
dc.subject.proposal.eng.fl_str_mv COVID-19 lockdown
Industrial city
Air quality
Potential source contribution function
topic COVID-19 lockdown
Industrial city
Air quality
Potential source contribution function
description To better understand the changes in air pollutants in an industrial city, Handan, North China, during the COVID-19 lockdown period, the air quality and meteorological conditions were recorded from 1 January to 3 March 2020 and the corresponding period in 2019. Compared to the corresponding period in 2019, the largest reduction in PM2.5–10, PM2.5, NO2 and CO occurred during the COVID-19 lockdown period. PM2.5–10 displayed the highest reduction (66.6%), followed by NO2 (58.4%) and PM2.5 (50.1%), while O3 increased by 13.9%. Similarly, compared with the pre-COVID-19 period, NO2 significantly decreased by 66.1% during the COVID-19 lockdown, followed by PM2.5–10 (45.9%) and PM2.5 (42.4%), while O3 increased significantly (126%). Among the different functional areas, PM2.5 and PM2.5–10 dropped the most in the commercial area during the COVID-19 lockdown. NO2 and SO2 decreased the most in the traffic and residential areas, respectively, while NO2 increased only in the township and SO2 increased the most in the industrial area. O3 increased in all functional areas to different extents. Potential source contribution function analysis indicated that not only the local air pollution lessened, but also long-distance or inter-regional transport contributed much less to heavy pollution during the lockdown period. These results indicate that the COVID-19 lockdown measures led to significantly reduced PM and NO2 but increased O3 , highlighting the importance of the synergetic control of PM2.5 and O3 , as well as regional joint prevention and the control of air pollution. Moreover, it is necessary to formulate air pollution control measures according to functional areas on a city scale.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-11-17T21:11:32Z
dc.date.available.none.fl_str_mv 2022-11-17T21:11:32Z
dc.date.issued.none.fl_str_mv 2022-09-14
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.content.spa.fl_str_mv Text
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/article
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.citation.spa.fl_str_mv Niu, H.; Zhang, C.; Hu, W.; Hu, T.; Wu, C.; Hu, S.; Silva, L.F.O.; Gao, N.; Bao, X.; Fan, J. Air Quality Changes during the COVID-19 Lockdown in an Industrial City in North China: Post-Pandemic Proposals for Air Quality Improvement. Sustainability 2022, 14, 11531. https://doi.org/10.3390/ su141811531
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11323/9626
dc.identifier.doi.none.fl_str_mv 10.3390/ su141811531
dc.identifier.eissn.spa.fl_str_mv 2071-1050
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv Niu, H.; Zhang, C.; Hu, W.; Hu, T.; Wu, C.; Hu, S.; Silva, L.F.O.; Gao, N.; Bao, X.; Fan, J. Air Quality Changes during the COVID-19 Lockdown in an Industrial City in North China: Post-Pandemic Proposals for Air Quality Improvement. Sustainability 2022, 14, 11531. https://doi.org/10.3390/ su141811531
10.3390/ su141811531
2071-1050
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/9626
https://repositorio.cuc.edu.co/
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.ispartofjournal.spa.fl_str_mv Sustainability
dc.relation.references.spa.fl_str_mv 1. Bu, X.; Xie, Z.; Liu, J.; Wei, L.; Wang, X.; Chen, M.; Ren, H. Global PM2.5 attributable health burden from 1990 to 2017: Estimates from the Global Burden of disease study 2017. Environ. Res. 2021, 197, 111123. [CrossRef] [PubMed]
2. Cheng, J.; Su, J.; Cui, T.; Li, X.; Dong, X.; Sun, F.; Yang, Y.; Tong, D.; Zheng, Y.; Li, Y.; et al. Dominant role of emission reduction in PM2.5 air quality improvement in Beijing during 2013–2017: A model-based decomposition analysis. Atmos. Chem. Phys. 2019, 19, 6125–6146. [CrossRef]
3. Yan, D.; Lei, Y.; Shi, Y.; Zhu, Q.; Li, L.; Zhang, Z. Evolution of the spatiotemporal pattern of PM2.5 concentrations in China-a case study from the Beijing-Tianjin-Hebei region. Atmos. Environ. 2018, 183, 225–233. [CrossRef]
4. Zeng, J.J.; Liu, T.; Feiock, R.; Li, F. The impacts of China’s provincial energy policies on major air pollutants: A spatial econometric analysis. Energy Policy 2019, 132, 392–403. [CrossRef]
5. Xue, F.; Niu, H.; Hu, S.; Wu, C.; Zhang, C.; Gao, N.; Ren, X.; Li, S.; Hu, W.; Wang, J.; et al. Seasonal variations and source apportionment of carbonaceous aerosol in PM2.5 from a coal mining city in the North China Plain. Energy Explor. Exploit. 2021, 40, 834–851. [CrossRef]
6. Song, X.; Jia, J.; Wu, F.; Niu, H.; Ma, Q.; Guo, B.; Shao, L.; Zhang, D. Local emissions and secondary pollutants cause severe PM2.5 elevation in urban air at the south edge of the North China Plain: Results from winter haze of 2017–2018 at a mega city. Sci. Total Environ. 2021, 802, 149630. [CrossRef]
7. Chen, S.; Yang, J.; Yang, W.; Wang, C.; Bärnighausen, T. COVID-19 control in China during mass population movements at New Year. Lancet 2020, 395, 764–766. [CrossRef]
8. Wang, Y.; Wen, Y.; Wang, Y.; Zhang, S.; Zhang, K.M.; Zheng, H.; Xing, J.; Wu, Y.; Hao, J. Four-month changes in air quality during and after the COVID-19 lockdown in six megacities in China. Environ. Sci. Technol. Lett. 2020, 7, 802–808. [CrossRef]
9. Tian, H.; Liu, Y.; Li, Y.; Wu, C.H.; Chen, B.; Kraemer, M.U.G.; Li, B.; Cai, J.; Xu, B.; Yang, Q.; et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science 2020, 368, 638–642. [CrossRef]
10. Wang, C.; Horby, P.W.; Hayden, F.G.; Gao, G.F. A novel coronavirus outbreak of global health concern. Lancet 2020, 395, 470–473. [CrossRef]
11. Huang, X.; Ding, A.; Gao, J.; Zheng, B.; Zhou, D.; Qi, X.; Tang, R.; Wang, J.; Ren, C.; Nie, W.; et al. Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China. Natl. Sci. Rev. 2021, 8, nwaa137. [CrossRef]
12. Zambrano-Monserrate, M.A.; Ruano, M.A.; Sanchez-Alcalde, L. Indirect effects of COVID-19 on the environment. Sci. Total Environ. 2020, 728, 138813. [CrossRef]
13. Shi, X.; Brasseur, G.P. The response in air quality to the reduction of Chinese economic activities during the COVID-19 outbreak. Geophys. Res. Lett. 2020, 47, e2020GL088070. [CrossRef]
14. Adam, M.G.; Tran, P.T.M.; Balasubramanian, R. Air quality changes in cities during the COVID-19 lockdown: A critical review. Atmos. Res. 2021, 264, 105823. [CrossRef]
15. Lelieveld, J.; Evans, J.S.; Fnais, M.; Giannadaki, D.; Pozzer, A. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 2015, 525, 367–371. [CrossRef]
16. Rahman, M.M.; Paul, K.C.; Hossain, M.A.; Ali, G.G.M.N.; Rahman, M.S.; Thill, J.C. Machine learning on the COVID-19 pandemic, human mobility and air quality: A review. IEEE Access 2021, 9, 72420–72450. [CrossRef]
17. Gamelas, C.; Abecasis, L.; Canha, N.; Almeida, S.M. The Impact of COVID-19 Confinement Measures on the Air Quality in an Urban-Industrial Area of Portugal. Atmosphere 2021, 12, 1097. [CrossRef]
18. Ropkins, K.; Tate, J.E. Early observations on the impact of the COVID-19 lockdown on air quality trends across the UK. Sci. Total Environ. 2021, 754, 142374. [CrossRef]
19. Wang, Q.; Li, S. Nonlinear impact of COVID-19 on pollutions—Evidence from Wuhan, New York, Milan, Madrid, Bandra, London, Tokyo and Mexico City. Sustain. Cities Soc. 2021, 65, 102629. [CrossRef]
20. Kroll, J.H.; Heald, C.L.; Cappa, C.D.; Farmer, D.K.; Fry, J.L.; Murphy, J.G.; Steiner, A.L. The complex chemical effects of COVID-19 shutdowns on air quality. Nat. Chem. 2020, 12, 777–779. [CrossRef]
21. He, G.; Pan, Y.; Tanaka, T. The short-term impacts of COVID-19 lockdown on urban air pollution in China. Nat. Sustain. 2020, 3, 1005–1011. [CrossRef]
22. Lian, X.; Huang, J.; Huang, R.; Liu, C.; Wang, L.; Zhang, T. Impact of city lockdown on the air quality of COVID-19-hit of Wuhan city. Sci. Total Environ. 2020, 742, 140556. [CrossRef]
23. Hu, X.; Liu, Q.; Fu, Q.; Xu, H.; Shen, Y.; Liu, D.; Wang, Y.; Jia, H.; Cheng, J. A high-resolution typical pollution source emission inventory and pollution source changes during the COVID-19 lockdown in a megacity, China. Environ. Sci. Pollut. Res. 2021, 28, 45344–45352. [CrossRef]
24. Zhang, K.; de Leeuw, G.; Yang, Z.; Chen, X.; Jiao, J. The impacts of the COVID-19 lockdown on air quality in the Guanzhong Basin, China. Remote Sens. 2020, 12, 3042. [CrossRef]
25. Wang, H.; Tan, Y.; Zhang, L.; Shen, L.; Zhao, T.; Dai, Q.; Guan, T.; Ke, Y.; Li, X. Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown. Atmos. Pollut. Res. 2021, 12, 101247. [CrossRef]
26. Pei, Z.; Han, G.; Ma, X.; Su, H.; Gong, W. Response of major air pollutants to COVID-19 lockdowns in China. Sci. Total Environ. 2020, 743, 140879. [CrossRef]
27. Niu, H.; Wu, Z.; Xue, F.; Liu, Z.; Hu, W.; Wang, J.; Fan, J.; Lu, Y. Seasonal variations and risk assessment of heavy metals in PM from Handan, China. World J. Eng. 2021, 18, 886–897. [CrossRef]
28. Polissar, A.V.; Hopke, P.K.; Paatero, P.; Kaufmann, Y.J.; Hall, D.K.; Bodhaine, B.A.; Dutton, E.G.; Harris, J.M. The aerosol at Barrow, Alaska: Long-term trends and source locations. Atmos. Environ. 1999, 33, 2441–2458. [CrossRef]
29. Abbott, M.L.; Lin, C.J.; Martian, P.; Einerson, J.J. Atmospheric mercury near Salmon Falls Creek Reservoir in southern Idaho. Appl. Geochem. 2008, 23, 438–453. [CrossRef]
30. Xu, X.; Akhtar, U. Identification of potential regional sources of atmospheric total gaseous mercury in Windsor, Ontario, Canada using hybrid receptor modeling. Atmos. Chem. Phys. 2010, 10, 7073–7083. [CrossRef]
31. Cheng, M.D.; Lin, C.J. Receptor modeling for smoke of 1998 biomass burning in Central America. J. Geophys. Res. 2001, 106, 22871–22886. [CrossRef]
32. Qiao, Z.; Wu, F.; Xu, X.; Yang, J.; Liu, L. Mechanism of spatiotemporal air quality response to meteorological parameters: A national-scale analysis in China. Sustainability 2019, 11, 3957. [CrossRef]
33. Pateraki, S.; Asimakopoulos, D.N.; Flocas, H.A.; Maggos, T.; Vasilakos, C. The role of meteorology on different sized aerosol fractions (PM10, PM2.5, PM2.5-10). Sci. Total Environ. 2012, 419, 124–135. [CrossRef] [PubMed]
34. Wang, Y.; Liu, C.; Wang, Q.; Qin, Q.; Ren, H.; Cao, J. Impacts of natural and socioeconomic factors on PM2.5 from 2014 to 2017. J. Environ. Manag. 2021, 284, 112071. [CrossRef]
35. Hu, W.; Hu, M.; Hu, W.W.; Zheng, J.; Chen, C.; Wu, Y.; Guo, S. Seasonal variations in high time-resolved chemical compositions, sources, and evolution of atmospheric submicron aerosols in the megacity Beijing. Atmos. Chem. Phys. 2017, 17, 9979–10000. [CrossRef]
36. Liu, F.; Zhang, G.; Lian, X.; Fu, Y.; Lin, Q.; Yang, Y.; Bi, X.; Wang, X.; Peng, P.; Sheng, G. Influence of meteorological parameters and oxidizing capacity on characteristics of airborne particulate amines in an urban area of the Pearl River Delta, China. Environ. Res. 2022, 212, 113212. [CrossRef]
37. Zhang, Q.; Zheng, Y.; Tong, D.; Shao, M.; Wang, S.; Zhang, Y.; Xu, X.; Wang, J.; He, H.; Liu, W.; et al. Drivers of improved PM2.5 air quality in China from 2013 to 2017. Proc. Natl. Acad. Sci. USA 2019, 116, 24463–24469. [CrossRef]
38. Zhang, X.; Xu, X.; Ding, Y.; Liu, Y.; Zhang, H.; Wang, Y.; Zhong, J. The impact of meteorological changes from 2013 to 2017 on PM2.5 mass reduction in key regions in China. Sci. China Earth Sci. 2019, 62, 1885–1902. [CrossRef]
39. Xing, J.; Li, S.; Jiang, Y.; Wang, S.; Ding, D.; Dong, Z.; Zhu, Y.; Hao, J. Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic on the North China Plain: A response modeling study. Atmos. Chem. Phys. 2020, 20, 14347–14359. [CrossRef]
40. Li, R.; Zhao, Y.; Fu, H.; Chen, J.; Peng, M.; Wang, C. Substantial changes in gaseous pollutants and chemical compositions in fine particles in the North China Plain during the COVID-19 lockdown period: Anthropogenic vs meteorological influences. Atmos. Chem. Phys. 2021, 21, 8677–8692. [CrossRef]
41. Chu, B.; Zhang, S.; Liu, J.; Ma, Q.; He, H. Significant concurrent decrease in PM2.5 and NO2 concentrations in China during COVID-19 epidemic. J. Environ. Sci. 2021, 99, 346–353. [CrossRef]
42. Yuan, Q.; Qi, B.; Hu, D.; Wang, J.; Zhang, J.; Yang, H.; Zhang, S.; Liu, L.; Xu, L.; Li, W. Spatiotemporal variations and reduction of air pollutants during the COVID-19 pandemic in a megacity of Yangtze River Delta in China. Sci. Total Environ. 2021, 751, 141820. [CrossRef]
43. Ding, J.; Dai, Q.; Li, Y.; Han, S.; Zhang, Y.; Feng, Y. Impact of meteorological condition changes on air quality and particulate chemical composition during the COVID-19 lockdown. J. Environ. Sci. 2021, 109, 45–56. [CrossRef]
44. Liu, L.; Zhang, J.; Du, R.; Teng, X.; Hu, R.; Yuan, Q.; Tang, S.; Ren, C.; Huang, X.; Xu, L.; et al. Chemistry of atmospheric fine particles during the COVID-19 pandemic in a megacity of eastern China. Geophys. Res. Lett. 2021, 48, 2020GL091611. [CrossRef]
45. Xu, M.; Qin, Z.; Zhang, S. Integrated assessment of cleaning air policy in China: A case study for Beijing-Tianjin-Hebei region. J. Clean. Prod. 2021, 296, 126596. [CrossRef]
46. Wu, Z.; Hu, T.; Hu, W.; Shao, L.; Sun, Y.; Xue, F.; Niu, H. Evolution in physico-chemical properties of fine particles emitted from residential coal combustion based on chamber experiment. Gondwana Res. 2022, 110, 252–263. [CrossRef]
47. Hu, B.; Duan, J.; Liu, S.; Hu, J.; Zhang, M.; Kang, P.; Wang, C. Evaluation of the Effect of Fireworks Prohibition in the BeijingTianjin-Hebei and Surrounding Areas during the Spring Festival of 2018. Res. Environ. Sci. 2019, 32, 203–211.
48. Xian, T.; Li, Z.; Wei, J. Changes in air pollution following the COVID-19 epidemic in Northern China: The role of meteorology. Front. Environ. Sci. 2021, 9, 654651. [CrossRef]
49. He, Z.; Liu, P.; Zhao, X.; He, X.; Liu, J.; Mu, Y. Responses of surface O3 and PM2.5 trends to changes of anthropogenic emissions in summer over Beijing during 2014-2019: A study based on multiple linear regression and WRF-Chem. Sci. Total Environ. 2021, 807, 150792. [CrossRef]
50. Wu, C.L.; Wang, H.W.; Cai, W.J.; He, H.D.; Ni, A.N.; Peng, Z.R. Impact of the COVID-19 lockdown on roadside traffic-related air pollution in Shanghai, China. Build. Environ. 2021, 194, 107718. [CrossRef]
51. Liu, Y.; Wang, T.; Stavrakou, T.; Elguindi, N.; Doumbia, T.; Granier, C.; Bouarar, I.; Gaubert, B.; Brasseur, G.P. Diverse response of surface ozone to COVID-19 lockdown in China. Sci. Total Environ. 2021, 789, 147739. [CrossRef] [PubMed]
52. Guo, X.; Wu, H.; Chen, D.; Ye, Z.; Shen, Y.; Liu, J.; Cheng, S. Estimation and prediction of pollutant emissions from agricultural and construction diesel machinery in the Beijing-Tianjin-Hebei (BTH) region, China. Environ. Pollut. 2020, 260, 113973. [CrossRef]
53. Zhang, L.; An, J.; Liu, M.; Li, Z.; Liu, Y.; Tao, L.; Liu, X.; Zhang, F.; Zheng, D.; Gao, Q.; et al. Spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing, China. Environ. Pollut. 2020, 262, 114276. [CrossRef]
54. Zheng, X.; Guo, B.; He, J.; Chen, S.X. Effects of corona virus disease-19 control measures on air quality in North China. Environmetrics 2021, 32, e2673. [CrossRef]
55. Sokhi, R.S.; Singh, V.; Querol, X.; Finardi, S.; Targino, A.C.; Andrade, M.F.; Pavlovic, R.; Garland, R.M.; Massague, J.; Kong, S.; et al. A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions. Environ. Int. 2021, 157, 106818. [CrossRef]
56. Hassler, B.; McDonald, B.C.; Frost, G.J.; Borbon, A.; Carslaw, D.C.; Civerolo, K.; Granier, C.; Monks, P.S.; Monks, S.; Parrish, D.D.; et al. Analysis of long-term observations of NOx and CO in megacities and application to constraining emissions inventories. Geophys. Res. Lett. 2016, 43, 9920–9930. [CrossRef]
57. Bai, Y.; Wang, Z.; Xie, F.; Cen, L.; Xie, Z.; Zhou, X.; He, J.; Lu, C. Changes in stoichiometric characteristics of ambient air pollutants pre-to post-COVID-19 in China. Environ. Res. 2022, 209, 112806. [CrossRef]
58. Zhang, Q.; Jiang, X.; Tong, D.; Davis, S.J.; Zhao, H.; Geng, G.; Feng, T.; Zheng, B.; Lu, Z.; Streets, D.G.; et al. Transboundary health impacts of transported global air pollution and international trade. Nature 2017, 543, 705–709. [CrossRef]
59. Ostro, B.; World Health Organization/Occupational Environmental Health Team. Outdoor Air Pollution: Assessing the Environmental Burden of Disease at National and Local Levels; World Health Organization: Geneva, Switzerland, 2004.
60. Zha, H.; Wang, R.; Feng, X.; An, C.; Qian, J. Spatial characteristics of the PM2.5/PM10 ratio and its indicative significance regarding air pollution in Hebei Province, China. Environ. Monit. Assess. 2021, 193, 486. [CrossRef]
61. Fu, S.; Guo, M.; Fan, L.; Deng, Q.; Han, D.; Wei, Y.; Luo, J.; Qin, G.; Cheng, J. Ozone pollution mitigation in guangxi (south China) driven by meteorology and anthropogenic emissions during the COVID-19 lockdown. Environ. Pollut. 2021, 272, 115927. [CrossRef]
62. Chang, X.; Wang, S.; Zhao, B.; Xing, J.; Liu, X.; Wei, L.; Song, Y.; Wu, W.; Cai, S.; Zheng, H.; et al. Contributions of inter-city and regional transport to PM2.5 concentrations in the Beijing-Tianjin-Hebei region and its implications on regional joint air pollution control. Sci. Total Environ. 2019, 660, 1191–1200. [CrossRef] [PubMed]
63. Zhang, Y.; Zhu, B.; Gao, J.; Kang, H.; Yang, P.; Wang, L.; Zhang, J. The Source Apportionment of Primary PM2.5 in an Aerosol Pollution Event over Beijing-Tianjin-Hebei Region using WRF-Chem, China. Aerosol Air Qual. Res. 2017, 17, 2966–2980. [CrossRef]
64. Cheng, Y.; Zhu, B.; Wang, L.; Lu, W.; Kang, H.; Gao, J. Source apportionments of black carbon induced by local and regional transport in the atmospheric boundary layer of the Yangtze River Delta under stable weather conditions. Sci. Total Environ. 2022, 840, 156517. [CrossRef] [PubMed]
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spelling Atribución 4.0 Internacional (CC BY 4.0)© 2022 by the authors. Licensee MDPI, Basel, Switzerland.https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Niu, Hongyaa020e30b31f530236ab2b6db3f4136c7Zhang, Chongchongac24e5276a7fe1fe6b68ad2c8a8f541eHu, Wei5963c362e66f28bcf5459662ecd8523d600Hu, Tafengc357fca2d515b654339f6a0368ae4b54600Wen, Chunmiao3e89429539d4929654db9e410ff105d8600Hu, Sihao724a49d4cd18a444032bc80ee714f78b600Silva Oliveira, Luis Felipe615225808861349d2b8b4aa0934855d9Gao, Nana5db39a5bfc46607c6a6eaf226b9a48acbao, xiaolei645b7fc1aec0f7cb703c3c9b42555a28600Fan, Jingsen5f2a36f2c6980a290bf66071876d64e96002022-11-17T21:11:32Z2022-11-17T21:11:32Z2022-09-14Niu, H.; Zhang, C.; Hu, W.; Hu, T.; Wu, C.; Hu, S.; Silva, L.F.O.; Gao, N.; Bao, X.; Fan, J. Air Quality Changes during the COVID-19 Lockdown in an Industrial City in North China: Post-Pandemic Proposals for Air Quality Improvement. Sustainability 2022, 14, 11531. https://doi.org/10.3390/ su141811531https://hdl.handle.net/11323/962610.3390/ su1418115312071-1050Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/To better understand the changes in air pollutants in an industrial city, Handan, North China, during the COVID-19 lockdown period, the air quality and meteorological conditions were recorded from 1 January to 3 March 2020 and the corresponding period in 2019. Compared to the corresponding period in 2019, the largest reduction in PM2.5–10, PM2.5, NO2 and CO occurred during the COVID-19 lockdown period. PM2.5–10 displayed the highest reduction (66.6%), followed by NO2 (58.4%) and PM2.5 (50.1%), while O3 increased by 13.9%. Similarly, compared with the pre-COVID-19 period, NO2 significantly decreased by 66.1% during the COVID-19 lockdown, followed by PM2.5–10 (45.9%) and PM2.5 (42.4%), while O3 increased significantly (126%). Among the different functional areas, PM2.5 and PM2.5–10 dropped the most in the commercial area during the COVID-19 lockdown. NO2 and SO2 decreased the most in the traffic and residential areas, respectively, while NO2 increased only in the township and SO2 increased the most in the industrial area. O3 increased in all functional areas to different extents. Potential source contribution function analysis indicated that not only the local air pollution lessened, but also long-distance or inter-regional transport contributed much less to heavy pollution during the lockdown period. These results indicate that the COVID-19 lockdown measures led to significantly reduced PM and NO2 but increased O3 , highlighting the importance of the synergetic control of PM2.5 and O3 , as well as regional joint prevention and the control of air pollution. Moreover, it is necessary to formulate air pollution control measures according to functional areas on a city scale.19 páginasapplication/pdfengMDPI AGSwitzerlandhttps://www.mdpi.com/2071-1050/14/18/11531Air quality changes during the COVID-19 lockdown in an industrial city in North China: post-pandemic proposals for air quality improvementArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85North ChinaSustainability1. Bu, X.; Xie, Z.; Liu, J.; Wei, L.; Wang, X.; Chen, M.; Ren, H. Global PM2.5 attributable health burden from 1990 to 2017: Estimates from the Global Burden of disease study 2017. Environ. Res. 2021, 197, 111123. [CrossRef] [PubMed]2. Cheng, J.; Su, J.; Cui, T.; Li, X.; Dong, X.; Sun, F.; Yang, Y.; Tong, D.; Zheng, Y.; Li, Y.; et al. Dominant role of emission reduction in PM2.5 air quality improvement in Beijing during 2013–2017: A model-based decomposition analysis. Atmos. Chem. Phys. 2019, 19, 6125–6146. [CrossRef]3. Yan, D.; Lei, Y.; Shi, Y.; Zhu, Q.; Li, L.; Zhang, Z. Evolution of the spatiotemporal pattern of PM2.5 concentrations in China-a case study from the Beijing-Tianjin-Hebei region. Atmos. Environ. 2018, 183, 225–233. [CrossRef]4. Zeng, J.J.; Liu, T.; Feiock, R.; Li, F. The impacts of China’s provincial energy policies on major air pollutants: A spatial econometric analysis. Energy Policy 2019, 132, 392–403. [CrossRef]5. Xue, F.; Niu, H.; Hu, S.; Wu, C.; Zhang, C.; Gao, N.; Ren, X.; Li, S.; Hu, W.; Wang, J.; et al. Seasonal variations and source apportionment of carbonaceous aerosol in PM2.5 from a coal mining city in the North China Plain. Energy Explor. Exploit. 2021, 40, 834–851. [CrossRef]6. Song, X.; Jia, J.; Wu, F.; Niu, H.; Ma, Q.; Guo, B.; Shao, L.; Zhang, D. Local emissions and secondary pollutants cause severe PM2.5 elevation in urban air at the south edge of the North China Plain: Results from winter haze of 2017–2018 at a mega city. Sci. Total Environ. 2021, 802, 149630. [CrossRef]7. Chen, S.; Yang, J.; Yang, W.; Wang, C.; Bärnighausen, T. COVID-19 control in China during mass population movements at New Year. Lancet 2020, 395, 764–766. [CrossRef]8. Wang, Y.; Wen, Y.; Wang, Y.; Zhang, S.; Zhang, K.M.; Zheng, H.; Xing, J.; Wu, Y.; Hao, J. Four-month changes in air quality during and after the COVID-19 lockdown in six megacities in China. Environ. Sci. Technol. Lett. 2020, 7, 802–808. [CrossRef]9. Tian, H.; Liu, Y.; Li, Y.; Wu, C.H.; Chen, B.; Kraemer, M.U.G.; Li, B.; Cai, J.; Xu, B.; Yang, Q.; et al. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China. Science 2020, 368, 638–642. [CrossRef]10. Wang, C.; Horby, P.W.; Hayden, F.G.; Gao, G.F. A novel coronavirus outbreak of global health concern. Lancet 2020, 395, 470–473. [CrossRef]11. Huang, X.; Ding, A.; Gao, J.; Zheng, B.; Zhou, D.; Qi, X.; Tang, R.; Wang, J.; Ren, C.; Nie, W.; et al. Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China. Natl. Sci. Rev. 2021, 8, nwaa137. [CrossRef]12. Zambrano-Monserrate, M.A.; Ruano, M.A.; Sanchez-Alcalde, L. Indirect effects of COVID-19 on the environment. Sci. Total Environ. 2020, 728, 138813. [CrossRef]13. Shi, X.; Brasseur, G.P. The response in air quality to the reduction of Chinese economic activities during the COVID-19 outbreak. Geophys. Res. Lett. 2020, 47, e2020GL088070. [CrossRef]14. Adam, M.G.; Tran, P.T.M.; Balasubramanian, R. Air quality changes in cities during the COVID-19 lockdown: A critical review. Atmos. Res. 2021, 264, 105823. [CrossRef]15. Lelieveld, J.; Evans, J.S.; Fnais, M.; Giannadaki, D.; Pozzer, A. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 2015, 525, 367–371. [CrossRef]16. Rahman, M.M.; Paul, K.C.; Hossain, M.A.; Ali, G.G.M.N.; Rahman, M.S.; Thill, J.C. Machine learning on the COVID-19 pandemic, human mobility and air quality: A review. IEEE Access 2021, 9, 72420–72450. [CrossRef]17. Gamelas, C.; Abecasis, L.; Canha, N.; Almeida, S.M. The Impact of COVID-19 Confinement Measures on the Air Quality in an Urban-Industrial Area of Portugal. Atmosphere 2021, 12, 1097. [CrossRef]18. Ropkins, K.; Tate, J.E. Early observations on the impact of the COVID-19 lockdown on air quality trends across the UK. Sci. Total Environ. 2021, 754, 142374. [CrossRef]19. Wang, Q.; Li, S. Nonlinear impact of COVID-19 on pollutions—Evidence from Wuhan, New York, Milan, Madrid, Bandra, London, Tokyo and Mexico City. Sustain. Cities Soc. 2021, 65, 102629. [CrossRef]20. Kroll, J.H.; Heald, C.L.; Cappa, C.D.; Farmer, D.K.; Fry, J.L.; Murphy, J.G.; Steiner, A.L. The complex chemical effects of COVID-19 shutdowns on air quality. Nat. Chem. 2020, 12, 777–779. [CrossRef]21. He, G.; Pan, Y.; Tanaka, T. The short-term impacts of COVID-19 lockdown on urban air pollution in China. Nat. Sustain. 2020, 3, 1005–1011. [CrossRef]22. Lian, X.; Huang, J.; Huang, R.; Liu, C.; Wang, L.; Zhang, T. Impact of city lockdown on the air quality of COVID-19-hit of Wuhan city. Sci. Total Environ. 2020, 742, 140556. [CrossRef]23. Hu, X.; Liu, Q.; Fu, Q.; Xu, H.; Shen, Y.; Liu, D.; Wang, Y.; Jia, H.; Cheng, J. A high-resolution typical pollution source emission inventory and pollution source changes during the COVID-19 lockdown in a megacity, China. Environ. Sci. Pollut. Res. 2021, 28, 45344–45352. [CrossRef]24. Zhang, K.; de Leeuw, G.; Yang, Z.; Chen, X.; Jiao, J. The impacts of the COVID-19 lockdown on air quality in the Guanzhong Basin, China. Remote Sens. 2020, 12, 3042. [CrossRef]25. Wang, H.; Tan, Y.; Zhang, L.; Shen, L.; Zhao, T.; Dai, Q.; Guan, T.; Ke, Y.; Li, X. Characteristics of air quality in different climatic zones of China during the COVID-19 lockdown. Atmos. Pollut. Res. 2021, 12, 101247. [CrossRef]26. Pei, Z.; Han, G.; Ma, X.; Su, H.; Gong, W. Response of major air pollutants to COVID-19 lockdowns in China. Sci. Total Environ. 2020, 743, 140879. [CrossRef]27. Niu, H.; Wu, Z.; Xue, F.; Liu, Z.; Hu, W.; Wang, J.; Fan, J.; Lu, Y. Seasonal variations and risk assessment of heavy metals in PM from Handan, China. World J. Eng. 2021, 18, 886–897. [CrossRef]28. Polissar, A.V.; Hopke, P.K.; Paatero, P.; Kaufmann, Y.J.; Hall, D.K.; Bodhaine, B.A.; Dutton, E.G.; Harris, J.M. The aerosol at Barrow, Alaska: Long-term trends and source locations. Atmos. Environ. 1999, 33, 2441–2458. [CrossRef]29. Abbott, M.L.; Lin, C.J.; Martian, P.; Einerson, J.J. Atmospheric mercury near Salmon Falls Creek Reservoir in southern Idaho. Appl. Geochem. 2008, 23, 438–453. [CrossRef]30. Xu, X.; Akhtar, U. Identification of potential regional sources of atmospheric total gaseous mercury in Windsor, Ontario, Canada using hybrid receptor modeling. Atmos. Chem. Phys. 2010, 10, 7073–7083. [CrossRef]31. Cheng, M.D.; Lin, C.J. Receptor modeling for smoke of 1998 biomass burning in Central America. J. Geophys. Res. 2001, 106, 22871–22886. [CrossRef]32. Qiao, Z.; Wu, F.; Xu, X.; Yang, J.; Liu, L. Mechanism of spatiotemporal air quality response to meteorological parameters: A national-scale analysis in China. Sustainability 2019, 11, 3957. [CrossRef]33. Pateraki, S.; Asimakopoulos, D.N.; Flocas, H.A.; Maggos, T.; Vasilakos, C. The role of meteorology on different sized aerosol fractions (PM10, PM2.5, PM2.5-10). Sci. Total Environ. 2012, 419, 124–135. [CrossRef] [PubMed]34. Wang, Y.; Liu, C.; Wang, Q.; Qin, Q.; Ren, H.; Cao, J. Impacts of natural and socioeconomic factors on PM2.5 from 2014 to 2017. J. Environ. Manag. 2021, 284, 112071. [CrossRef]35. Hu, W.; Hu, M.; Hu, W.W.; Zheng, J.; Chen, C.; Wu, Y.; Guo, S. Seasonal variations in high time-resolved chemical compositions, sources, and evolution of atmospheric submicron aerosols in the megacity Beijing. Atmos. Chem. Phys. 2017, 17, 9979–10000. [CrossRef]36. Liu, F.; Zhang, G.; Lian, X.; Fu, Y.; Lin, Q.; Yang, Y.; Bi, X.; Wang, X.; Peng, P.; Sheng, G. Influence of meteorological parameters and oxidizing capacity on characteristics of airborne particulate amines in an urban area of the Pearl River Delta, China. Environ. Res. 2022, 212, 113212. [CrossRef]37. Zhang, Q.; Zheng, Y.; Tong, D.; Shao, M.; Wang, S.; Zhang, Y.; Xu, X.; Wang, J.; He, H.; Liu, W.; et al. Drivers of improved PM2.5 air quality in China from 2013 to 2017. Proc. Natl. Acad. Sci. USA 2019, 116, 24463–24469. [CrossRef]38. Zhang, X.; Xu, X.; Ding, Y.; Liu, Y.; Zhang, H.; Wang, Y.; Zhong, J. The impact of meteorological changes from 2013 to 2017 on PM2.5 mass reduction in key regions in China. Sci. China Earth Sci. 2019, 62, 1885–1902. [CrossRef]39. Xing, J.; Li, S.; Jiang, Y.; Wang, S.; Ding, D.; Dong, Z.; Zhu, Y.; Hao, J. Quantifying the emission changes and associated air quality impacts during the COVID-19 pandemic on the North China Plain: A response modeling study. Atmos. Chem. Phys. 2020, 20, 14347–14359. [CrossRef]40. Li, R.; Zhao, Y.; Fu, H.; Chen, J.; Peng, M.; Wang, C. Substantial changes in gaseous pollutants and chemical compositions in fine particles in the North China Plain during the COVID-19 lockdown period: Anthropogenic vs meteorological influences. Atmos. Chem. Phys. 2021, 21, 8677–8692. [CrossRef]41. Chu, B.; Zhang, S.; Liu, J.; Ma, Q.; He, H. Significant concurrent decrease in PM2.5 and NO2 concentrations in China during COVID-19 epidemic. J. Environ. Sci. 2021, 99, 346–353. [CrossRef]42. Yuan, Q.; Qi, B.; Hu, D.; Wang, J.; Zhang, J.; Yang, H.; Zhang, S.; Liu, L.; Xu, L.; Li, W. Spatiotemporal variations and reduction of air pollutants during the COVID-19 pandemic in a megacity of Yangtze River Delta in China. Sci. Total Environ. 2021, 751, 141820. [CrossRef]43. Ding, J.; Dai, Q.; Li, Y.; Han, S.; Zhang, Y.; Feng, Y. Impact of meteorological condition changes on air quality and particulate chemical composition during the COVID-19 lockdown. J. Environ. Sci. 2021, 109, 45–56. [CrossRef]44. Liu, L.; Zhang, J.; Du, R.; Teng, X.; Hu, R.; Yuan, Q.; Tang, S.; Ren, C.; Huang, X.; Xu, L.; et al. Chemistry of atmospheric fine particles during the COVID-19 pandemic in a megacity of eastern China. Geophys. Res. Lett. 2021, 48, 2020GL091611. [CrossRef]45. Xu, M.; Qin, Z.; Zhang, S. Integrated assessment of cleaning air policy in China: A case study for Beijing-Tianjin-Hebei region. J. Clean. Prod. 2021, 296, 126596. [CrossRef]46. Wu, Z.; Hu, T.; Hu, W.; Shao, L.; Sun, Y.; Xue, F.; Niu, H. Evolution in physico-chemical properties of fine particles emitted from residential coal combustion based on chamber experiment. Gondwana Res. 2022, 110, 252–263. [CrossRef]47. Hu, B.; Duan, J.; Liu, S.; Hu, J.; Zhang, M.; Kang, P.; Wang, C. Evaluation of the Effect of Fireworks Prohibition in the BeijingTianjin-Hebei and Surrounding Areas during the Spring Festival of 2018. Res. Environ. Sci. 2019, 32, 203–211.48. Xian, T.; Li, Z.; Wei, J. Changes in air pollution following the COVID-19 epidemic in Northern China: The role of meteorology. Front. Environ. Sci. 2021, 9, 654651. [CrossRef]49. He, Z.; Liu, P.; Zhao, X.; He, X.; Liu, J.; Mu, Y. Responses of surface O3 and PM2.5 trends to changes of anthropogenic emissions in summer over Beijing during 2014-2019: A study based on multiple linear regression and WRF-Chem. Sci. Total Environ. 2021, 807, 150792. [CrossRef]50. Wu, C.L.; Wang, H.W.; Cai, W.J.; He, H.D.; Ni, A.N.; Peng, Z.R. Impact of the COVID-19 lockdown on roadside traffic-related air pollution in Shanghai, China. Build. Environ. 2021, 194, 107718. [CrossRef]51. Liu, Y.; Wang, T.; Stavrakou, T.; Elguindi, N.; Doumbia, T.; Granier, C.; Bouarar, I.; Gaubert, B.; Brasseur, G.P. Diverse response of surface ozone to COVID-19 lockdown in China. Sci. Total Environ. 2021, 789, 147739. [CrossRef] [PubMed]52. Guo, X.; Wu, H.; Chen, D.; Ye, Z.; Shen, Y.; Liu, J.; Cheng, S. Estimation and prediction of pollutant emissions from agricultural and construction diesel machinery in the Beijing-Tianjin-Hebei (BTH) region, China. Environ. Pollut. 2020, 260, 113973. [CrossRef]53. Zhang, L.; An, J.; Liu, M.; Li, Z.; Liu, Y.; Tao, L.; Liu, X.; Zhang, F.; Zheng, D.; Gao, Q.; et al. Spatiotemporal variations and influencing factors of PM2.5 concentrations in Beijing, China. Environ. Pollut. 2020, 262, 114276. [CrossRef]54. Zheng, X.; Guo, B.; He, J.; Chen, S.X. Effects of corona virus disease-19 control measures on air quality in North China. Environmetrics 2021, 32, e2673. [CrossRef]55. Sokhi, R.S.; Singh, V.; Querol, X.; Finardi, S.; Targino, A.C.; Andrade, M.F.; Pavlovic, R.; Garland, R.M.; Massague, J.; Kong, S.; et al. A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions. Environ. Int. 2021, 157, 106818. [CrossRef]56. Hassler, B.; McDonald, B.C.; Frost, G.J.; Borbon, A.; Carslaw, D.C.; Civerolo, K.; Granier, C.; Monks, P.S.; Monks, S.; Parrish, D.D.; et al. Analysis of long-term observations of NOx and CO in megacities and application to constraining emissions inventories. Geophys. Res. Lett. 2016, 43, 9920–9930. [CrossRef]57. Bai, Y.; Wang, Z.; Xie, F.; Cen, L.; Xie, Z.; Zhou, X.; He, J.; Lu, C. Changes in stoichiometric characteristics of ambient air pollutants pre-to post-COVID-19 in China. Environ. Res. 2022, 209, 112806. [CrossRef]58. Zhang, Q.; Jiang, X.; Tong, D.; Davis, S.J.; Zhao, H.; Geng, G.; Feng, T.; Zheng, B.; Lu, Z.; Streets, D.G.; et al. Transboundary health impacts of transported global air pollution and international trade. Nature 2017, 543, 705–709. [CrossRef]59. Ostro, B.; World Health Organization/Occupational Environmental Health Team. Outdoor Air Pollution: Assessing the Environmental Burden of Disease at National and Local Levels; World Health Organization: Geneva, Switzerland, 2004.60. Zha, H.; Wang, R.; Feng, X.; An, C.; Qian, J. Spatial characteristics of the PM2.5/PM10 ratio and its indicative significance regarding air pollution in Hebei Province, China. Environ. Monit. Assess. 2021, 193, 486. [CrossRef]61. Fu, S.; Guo, M.; Fan, L.; Deng, Q.; Han, D.; Wei, Y.; Luo, J.; Qin, G.; Cheng, J. Ozone pollution mitigation in guangxi (south China) driven by meteorology and anthropogenic emissions during the COVID-19 lockdown. Environ. Pollut. 2021, 272, 115927. [CrossRef]62. Chang, X.; Wang, S.; Zhao, B.; Xing, J.; Liu, X.; Wei, L.; Song, Y.; Wu, W.; Cai, S.; Zheng, H.; et al. Contributions of inter-city and regional transport to PM2.5 concentrations in the Beijing-Tianjin-Hebei region and its implications on regional joint air pollution control. Sci. Total Environ. 2019, 660, 1191–1200. [CrossRef] [PubMed]63. Zhang, Y.; Zhu, B.; Gao, J.; Kang, H.; Yang, P.; Wang, L.; Zhang, J. The Source Apportionment of Primary PM2.5 in an Aerosol Pollution Event over Beijing-Tianjin-Hebei Region using WRF-Chem, China. Aerosol Air Qual. Res. 2017, 17, 2966–2980. [CrossRef]64. Cheng, Y.; Zhu, B.; Wang, L.; Lu, W.; Kang, H.; Gao, J. Source apportionments of black carbon induced by local and regional transport in the atmospheric boundary layer of the Yangtze River Delta under stable weather conditions. Sci. Total Environ. 2022, 840, 156517. [CrossRef] [PubMed]1911814COVID-19 lockdownIndustrial cityAir qualityPotential source contribution functionORIGINALAir Quality Changes during the COVID-19 Lockdown in an Industrial City in North China.pdfAir Quality Changes during the COVID-19 Lockdown in an Industrial City in North China.pdfArtículoapplication/pdf3727264https://repositorio.cuc.edu.co/bitstream/11323/9626/1/Air%20Quality%20Changes%20during%20the%20COVID-19%20Lockdown%20in%20an%20Industrial%20City%20in%20North%20China.pdfc77aebb5370a788442dcdc46d66e24c7MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://repositorio.cuc.edu.co/bitstream/11323/9626/2/license.txt2f9959eaf5b71fae44bbf9ec84150c7aMD52open accessTEXTAir Quality Changes during the COVID-19 Lockdown in an Industrial City in North China.pdf.txtAir Quality Changes during the COVID-19 Lockdown in an Industrial City in North China.pdf.txtExtracted 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corporada en las Obras Colectivas.

b.	Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.

c.	Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.
Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).

4. Restricciones.
La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:

a.	Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).

b.	Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.

c.	Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.

d.	Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:

i.	Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.

ii.	Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.

e.	Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.

5. Representaciones, Garantías y Limitaciones de Responsabilidad.
A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

6. Limitación de responsabilidad.
A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

7. Término.

a.	Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.

b.	Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.

8. Varios.

a.	Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.

b.	Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.

c.	Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.

d.	Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.
0000-0003-3297-6991724a49d4cd18a444032bc80ee714f78b600

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