Articles | Volume 25, issue 6
https://doi.org/10.5194/acp-25-3583-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-3583-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Construction and application of a pollen emissions model based on phenology and random forests
Jiangtao Li
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai, 200438, China
Xingqin An
CORRESPONDING AUTHOR
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Zhaobin Sun
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Caihua Ye
Meteorological Service Center of Beijing Meteorological Bureau, Beijing, 100089, China
Qing Hou
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Yuxin Zhao
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Zhe Liu
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China
Related authors
No articles found.
Zhaobin Sun, Xiujuan Zhao, Ziming Li, Guiqian Tang, and Shiguang Miao
Atmos. Chem. Phys., 21, 8863–8882, https://doi.org/10.5194/acp-21-8863-2021, https://doi.org/10.5194/acp-21-8863-2021, 2021
Short summary
Short summary
Different weather types will shape significantly different structures of the pollution boundary layer. The findings of this study allow us to understand the inherent difference among heavy pollution boundary layers; in addition, they reveal the formation mechanism of haze pollution from an integrated synoptic-scale and boundary layer structure perspective.
Cited articles
Aerts, R., Stas, M., Vanlessen, N., Hendrickx, M., Bruffaerts, N., Hoebeke, L., Dendoncker, N., Dujardin, S., Saenen, N. D., Van Nieuwenhuyse, A., Aerts, J.-M., Van Orshoven, J., Nawrot, T. S., and Somers, B.: Residential green space and seasonal distress in a cohort of tree pollen allergy patients, Int. J. Hygien. Environ. Health, 223, 71–79, https://doi.org/10.1016/j.ijheh.2019.10.004, 2020.
Ahmed, A., Hakim, A., and Becker, A.: Evaluation of eczema, asthma, allergic rhinitis and allergies among the Grade-1 children of Iqaluit, Allerg. Asthma Clin. Immunol., 14, 9, https://doi.org/10.1186/s13223-018-0232-2, 2018.
Asher, M. I., Montefort, S., Björkstén, B., Lai, C. K. W., Strachan, D. P., Weiland, S. K., and Williams, H.: Worldwide time trends in the prevalence of symptoms of asthma, allergic rhinoconjunctivitis, and eczema in childhood: ISAAC Phases One and Three repeat multicountry cross-sectional surveys, Lancet, 368, 733–743, https://doi.org/10.1016/S0140-6736(06)69283-0, 2006.
Bai, Y., Liu, A., Sun, M., Liu, G., and Meng, Y.: Effect of Pollen Pollution on Human Health, J. Anhui Agri. Sci., 37, 2220–2222, 2009.
Bastl, K., Kmenta, M., Berger, M., and Berger, U.: The connection of pollen concentrations and crowd-sourced symptom data: new insights from daily and seasonal symptom load index data from 2013 to 2017 in Vienna, World Allerg. Org. J., 11, 24, https://doi.org/10.1186/s40413-018-0203-6, 2018.
Bishan, C., Bing, L., Chixin, C., Junxia, S., Shulin, Z., Cailang, L., Siqiao, Y., and Chuanxiu, L.: Relationship between airborne pollen assemblages and major meteorological parameters in Zhanjiang, South China, PLOS ONE, 15, e0240160, https://doi.org/10.1371/journal.pone.0240160, 2020.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Chen, H., Li, J., Cheng, L., Gao, Z. s., Lin, X., Zhu, R., Yang, L., Tao, A., Hong, H., Tang, W., Guo, Y., Huang, H., Sun, J.-l., Lai, H., Lei, C., Liu, G., Xiang, L., Chen, Z., Ma, H., Chan, A. W.-M., Hao, C., and Sun, B.: China Consensus Document on Allergy Diagnostics, Allerg.Asthma Immunol. Res., 13, 177–205, 2020.
Chen, J., Zhu, S., Wang, P., Zheng, Z., Shi, S., Li, X., Xu, C., Yu, K., Chen, R., Kan, H., Zhang, H., and Meng, X.: Predicting particulate matter, nitrogen dioxide, and ozone across Great Britain with high spatiotemporal resolution based on random forest models, Sci. Total Environ., 926, 171831, https://doi.org/10.1016/j.scitotenv.2024.171831, 2024.
Chen, Y. Z. and National Cooperation Group On Childhood Asthma: A nationwide survey in China on prevalence of asthma in urban children, Chin. J. Pediatr., 41, 123–127, 2003.
Cingi, C., Gevaert, P., Mösges, R., Rondon, C., Hox, V., Rudenko, M., Muluk, N. B., Scadding, G., Manole, F., Hupin, C., Fokkens, W. J., Akdis, C., Bachert, C., Demoly, P., Mullol, J., Muraro, A., Papadopoulos, N., Pawankar, R., Rombaux, P., Toskala, E., Kalogjera, L., Prokopakis, E., Hellings, P. W., and Bousquet, J.: Multi-morbidities of allergic rhinitis in adults: European Academy of Allergy and Clinical Immunology Task Force Report, Clin. Transl. Allerg., 7, 17, https://doi.org/10.1186/s13601-017-0153-z, 2017.
D'Amato, G., Vitale, C., Lanza, M., Molino, A., and D'Amato, M.: Climate change, air pollution, and allergic respiratory diseases: an update, Curr. Opin. Allerg. Clin. Immunol., 16, 434–440, https://doi.org/10.1097/aci.0000000000000301, 2016.
Damialis, A., Fotiou, C., Halley, J. M., and Vokou, D.: Effects of environmental factors on pollen production in anemophilous woody species, Trees, 25, 253–264, 2011.
Emanuel, M. B.: Hay fever, a post industrial revolution epidemic: a history of its growth during the 19th century, Clin. Exp. Allerg., 18, 295–304, https://doi.org/10.1111/j.1365-2222.1988.tb02872.x, 1988.
Frei, T. and Gassner, E.: Climate change and its impact on birch pollen quantities and the start of the pollen season an example from Switzerland for the period 1969–2006, Int. J. Biometeorol., 52, 667–674, https://doi.org/10.1007/s00484-008-0159-2, 2008.
Gao, Q. Q., Gao, Q. Y., Li, J., Shen, F., Ji, S., and Guan, L.: Preliminary Study on the Variation Characteristics of Pollen Concentration and Pollen Allergy Grade in Langfang Area in Spring, J. Agricult. Catastrophol., 12, 16–18, 2022.
Gu, D. and Liao, K.: The relationship between urban pollen dispersal and meteorological conditions, Hubei Meteorol., 3, 36–37, 2003.
Guan, L., Gao, Q. Y., Li, H., Li, J., and Gao, Q. Q.: Characteristics of Airborne Pollen Variation in Langfang City and Its Relationship with Meteorological Factors, Agricult. Technol. Serv., 38, 93–98, 2021.
Guzman, A., Tonelli, L. H., Roberts, D., Stiller, J. W., Jackson, M. A., Soriano, J. J., Yousufi, S., Rohan, K. J., Komarow, H., and Postolache, T. T.: Mood-worsening with high-pollen-counts and seasonality: A preliminary report, J. Affect. Disord., 101, 269–274, https://doi.org/10.1016/j.jad.2006.11.026, 2007.
He, H., Zhang, D., and Qiao, B.: Preliminary approach of the relationship between Airborne pollen amount and meteorological factors in Beijing urban area, Chin. J. Microbiol. Immunol., S2, 36–38, 2001.
He, X., Liu, D., Pan, Y., He, X., Zhang, M., and Yang, S.: Distribution and sources of fluvial pollen in the middle reaches of the Yellow River in China and their relationship with vegetation and land use, Sci. Total Environ., 856, 159109, https://doi.org/10.1016/j.scitotenv.2022.159109, 2023.
Helbig, N., Vogel, B., Vogel, H., and Fiedler, F.: Numerical modelling of pollen dispersion on the regional scale, Aerobiologia, 20, 3–19, https://doi.org/10.1023/B:AERO.0000022984.51588.30, 2004.
Ibrahim, N. M., Almarzouqi, F. I., Al Melaih, F. A., Farouk, H., Alsayed, M., and AlJassim, F. M.: Prevalence of asthma and allergies among children in the United Arab Emirates: A cross-sectional study, World Allerg. Org. J., 14, 100588, https://doi.org/10.1016/j.waojou.2021.100588, 2021.
Khwarahm, N. R., Dash, J., Skjøth, C. A., Newnham, R. M., Adams-Groom, B., Head, K., Caulton, E., and Atkinson, P. M.: Mapping the birch and grass pollen seasons in the UK using satellite sensor time-series, Sci. Total Environ., 578, 586-600, https://doi.org/10.1016/j.scitotenv.2016.11.004, 2017.
Krishna, M. T., Mahesh, P. A., Vedanthan, P. K., Mehta, V., Moitra, S., and Christopher, D. J.: The burden of allergic diseases in the Indian subcontinent: barriers and challenges, Lancet Glob. Health, 8, e478–e479, https://doi.org/10.1016/s2214-109x(20)30061-9, 2020.
Kurganskiy, A., Creer, S., de Vere, N., Griffith, G. W., Osborne, N. J., Wheeler, B. W., McInnes, R. N., Clewlow, Y., Barber, A., Brennan, G. L., Hanlon, H. M., Hegarty, M., Potter, C., Rowney, F., Adams-Groom, B., Petch, G. M., Pashley, C. H., Satchwell, J., de Weger, L. A., Rasmussen, K., Oliver, G., Sindt, C., Bruffaerts, N., and Skjøth, C. A.: Predicting the severity of the grass pollen season and the effect of climate change in Northwest Europe, Sci. Adv., 7, eabd7658, https://doi.org/10.1126/sciadv.abd7658, 2021.
Lake, I. R., Jones, N. R., Agnew, M., Goodess, C. M., Giorgi, F., Hamaoui-Laguel, L., Semenov, M. A., Solmon, F., Storkey, J., Vautard, R., and Epstein, M. M.: Climate Change and Future Pollen Allergy in Europe, Environ. Health Perspect., 125, 385–391, https://doi.org/10.1289/ehp173, 2017.
Lei, Y., Miao, Y., Zhao, Y., Zhang, S., Cao, H., Lan, X., Zhang, Z., and Jin, H.: The effects of meteorological conditions on allergenic airborne pollen in arid Northwest China, Atmos. Environ., 299, 119647, https://doi.org/10.1016/j.atmosenv.2023.119647, 2023.
Li, L., Hao, D., Li, X., Chen, M., Zhou, Y., Jurgens, D., Asrar, G., and Sapkota, A.: Satellite-based phenology products and in-situ pollen dynamics: A comparative assessment, Environ. Res., 204, 111937, https://doi.org/10.1016/j.envres.2021.111937, 2022.
Li, X., Zhou, Y., Meng, L., Asrar, G., Sapkota, A., and Coates, F.: Characterizing the relationship between satellite phenology and pollen season: A case study of birch, Remote Sens. Environ., 222, 267–274, https://doi.org/10.1016/j.rse.2018.12.036, 2019.
Li, Z., Chen, Y., Tao, Y., Zhao, X., Wang, D., Wei, T., Hou, Y., and Xu, X.: Mapping the personal PM2.5 exposure of China's population using random forest, Sci. Total Environ., 871, 162090, https://doi.org/10.1016/j.scitotenv.2023.162090, 2023.
Lou, H., Ma, S., Zhao, Y., Cao, F., He, F., Liu, Z., Bousquet, J., Wang, C., Zhang, L., and Bachert, C.: Sensitization patterns and minimum screening panels for aeroallergens in self-reported allergic rhinitis in China, Sci. Rep., 7, 9286, https://doi.org/10.1038/s41598-017-10111-9, 2017.
Mallol, J., Crane, J., von Mutius, E., Odhiambo, J., Keil, U., and Stewart, A.: The International Study of Asthma and Allergies in Childhood (ISAAC) Phase Three: A global synthesis, Allergolog. Immunopathol., 41, 73–85, https://doi.org/10.1016/j.aller.2012.03.001, 2013.
Meier, M. and Bigler, C.: Process-oriented models of autumn leaf phenology: ways to sound calibration and implications of uncertain projections, Geosci. Model Dev., 16, 7171–7201, https://doi.org/10.5194/gmd-16-7171-2023, 2023.
Meng, L., Wang, X., Ouyang, Z., Ren, Y., and Wang, Q.: Seasonal Dynamics of Airborne Pollens and Its Relationship with Meteorological Factors in Beijing Urban Area, Environ. Sci., 37, 452–458, 2016.
Mir, E., Panjabi, C., and Shah, A. K.: Impact of allergic rhinitis in school going children, Asia Pacif. Allerg., 2, 93–100, 2012.
Mo, Y., Zhang, J., Jiang, H., and Fu, Y. H.: A comparative study of 17 phenological models to predict the start of the growing season, Front. Forests Global Change, 5, 1032066, https://doi.org/10.3389/ffgc.2022.1032066, 2023.
National Cooperative Group on Childhood Asthma: A nationwide surrey on the prevalence of asthma among 0–14 year old population in China (1988–1990), Chin. J. Tuberc. Respir. Dis., 16, 64–68, 1993.
National Cooperative Group on Childhood Asthma, Institute of Environmental Health and Related Product Safety, Chinese Center for Disease Control and Prevention, and Chinese Center for Disease Control and Prevention: Third nationwide survey of childhood asthma in urban areas of China, Chin. J. Pediatr., 51, 729–735, 2013.
National Meteorological Science Data Center: China Meteorological Data Network, https://data.cma.cn/data/cdcindex/cid/f0fb4b55508804ca.html (last access: 20 March 2025), 2025.
Oleson, K., Lawrence, D., Bonan, G., Flanner, M., Kluzek, E., Lawrence, P., Levis, S., Swenson, S., Thornton, P., Dai, A., Decker, M., Dickinson, R., Feddema, J., Heald, C., Hoffman, F., Lamarque, J., Mahowald, N., Niu, G., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A., Stöckli, R., Wang, A., Yang, Z., Zeng, X. D., and Zeng, X. B.: Technical Description of Version 4.0 of the Community Land Model (CLM), University Corporation for Atmospheric Research, https://doi.org/10.5065/D6FB50WZ, 2010.
Qiao, Y., Wu, L., Yang, S., Wang, Q., Gu, H., Wei, L., Liu, G., Zhou, S., Wang, P., and Song, M.: Metabolomic and transcriptomic analyses provide insights into variations in flavonoids contents between two Artemisia cultivars, BMC Plant Biol., 23, 288, https://doi.org/10.1186/s12870-023-04295-8, 2023.
Rahman, A., Luo, C., Chen, B., Haberle, S., Khan, M. H. R., Jiang, W., Xiang, R., Liu, J., Wang, L., Lin, G., Yang, M., and Thilakanayaka, V.: Regional and seasonal variation of airborne pollen and spores among the cities of South China, Ac. Ecolog. Sin., 40, 283–295, https://doi.org/10.1016/j.chnaes.2019.05.012, 2020.
Schmidt, C. W.: Pollen Overload: Seasonal Allergies in a Changing Climate, Environ. Health Perspect., 124, 70–75, https://doi.org/10.1289/ehp.124-A70, 2016.
Septembre-Malaterre, A., Lalarizo Rakoto, M., Marodon, C., Bedoui, Y., Nakab, J., Simon, E., Hoarau, L., Savriama, S., Strasberg, D., Guiraud, P., Selambarom, J., and Gasque, P.: Artemisia annua, a Traditional Plant Brought to Light, Int. J. Mol. Sci., 21, 4986, https://doi.org/10.3390/ijms21144986, 2020.
Sofiev, M., Siljamo, P., Ranta, H., and Rantio-Lehtimäki, A.: Towards numerical forecasting of long-range air transport of birch pollen: theoretical considerations and a feasibility study, Int. J. Biometeorol., 50, 392–402, https://doi.org/10.1007/s00484-006-0027-x, 2006.
Sofiev, M., Siljamo, P., Ranta, H., Linkosalo, T., Jaeger, S. R., Rasmussen, A., Rantio-Lehtimäki, A., Severova, E. E., and Kukkonen, J.: A numerical model of birch pollen emission and dispersion in the atmosphere. Description of the emission module, Int. J. Biometeorol., 57, 45–58, 2013.
Solmon, F., Giorgi, F., and Liousse, C.: Aerosol modelling for regional climate studies: application to anthropogenic particles and evaluation over a European/African domain, Tellus B, 58, 51–72, https://doi.org/10.1111/j.1600-0889.2005.00155.x, 2006.
Stas, M., Aerts, R., Hendrickx, M., Delcloo, A., Dendoncker, N., Dujardin, S., Linard, C., Nawrot, T., Van Nieuwenhuyse, A., Aerts, J.-M., Van Orshoven, J., and Somers, B.: Exposure to green space and pollen allergy symptom severity: A case-crossover study in Belgium, Sci. Total Environ., 781, 146682, https://doi.org/10.1016/j.scitotenv.2021.146682, 2021.
Valipour Shokouhi, B., de Hoogh, K., Gehrig, R., and Eeftens, M.: Estimation of historical daily airborne pollen concentrations across Switzerland using a spatio temporal random forest model, Sci. Total Environ., 906, 167286, https://doi.org/10.1016/j.scitotenv.2023.167286, 2024.
Virro, H., Kmoch, A., Vainu, M., and Uuemaa, E.: Random forest-based modeling of stream nutrients at national level in a data-scarce region, Sci. Total Environ., 840, 156613, https://doi.org/10.1016/j.scitotenv.2022.156613, 2022.
Wang, X. D., Zheng, M., Lou, H. F., Wang, C. S., Zhang, Y., Bo, M. Y., Ge, S. Q., Zhang, N., Zhang, L., and Bachert, C.: An increased prevalence of self-reported allergic rhinitis in major Chinese cities from 2005 to 2011, Allergy, 71, 1170–1180, https://doi.org/10.1111/all.12874, 2016.
Wang, X. Y., Ma, T. T., Wang, X. Y., Zhuang, Y., Wang, X. D., Ning, H. Y., Shi, H. Y., Yu, R. L., Yan, D., Huang, H. D., Bai, Y. F., Shan, G. L., Zhang, B., Song, Q. K., Zhang, Y. F., Zhang, T. J., Jia, D. Z., Liu, X. L., Kang, Z. X., Yan, W. J., Yang, B. T., Bao, X. Z., Sun, S. H., Zhang, F. F., Yu, W. H., Bai, C. L., Wei, T., Yang, T., Ma, T. Q., Wu, X. B., Liu, J. G., Du, H., Zhang, L., Yan, Y., and Wang, D. Y.: Prevalence of pollen-induced allergic rhinitis with high pollen exposure in grasslands of northern China, Allergy, 73, 1232–1243, https://doi.org/10.1111/all.13388, 2018.
Wozniak, M. C. and Steiner, A. L.: A prognostic pollen emissions model for climate models (PECM1.0), Geosci. Model Dev., 10, 4105–4127, https://doi.org/10.5194/gmd-10-4105-2017, 2017.
Wu, Z., Liu, A., Bai, Y., Liu, B., and Wang, C.: Study on Evaluation of Economic Benefitsfrom Pollen Forecast and Service in Tianjin, Meteorol. Month., 37, 626–632, 2011.
Yin, J., Yue, F. M., Wang, L. L., He, H. J., Xu, T., Zhang, H. Y., Li, H., Wen, L. P., Sun, J. L., Gu, J. Q., Han, S. M., and Ye, S. T.: The clinical study of the relationship between allergic rhinitis and allergic asthma in the patients with autumnal pollinosis, Zhonghua Yi Xue Za Zhi, 85, 1683–1687, 2005.
Yorimitsu, Y., Kadosono, A., Hatakeyama, Y., Yabiku, T., and Ueno, O.: Transition from C3 to proto-Kranz to C3–C4 intermediate type in the genus Chenopodium (Chenopodiaceae), J. Plant Res., 132, 839–855, https://doi.org/10.1007/s10265-019-01135-5, 2019.
Zhang, Y. and Steiner, A. L.: Projected climate-driven changes in pollen emission season length and magnitude over the continental United States, Nat. Commun., 13, 1234, https://doi.org/10.1038/s41467-022-28764-0, 2022.
Zhao, Y., Sun, Z., Xiang, L., An, X., Hou, X., Shang, J., Han, L., and Ye, C.: Effects of pollen concentration on allergic rhinitis in children: A retrospective study from Beijing, a Chinese megacity, Environ. Res., 229, 115903, https://doi.org/10.1016/j.envres.2023.115903, 2023.
Short summary
Climate change and pollution have intensified pollen allergies. We developed a pollen emissions model using phenology and random forests. Key factors affecting annual pollen emissions include temperature, relative humidity and sunshine hours. Pollen dispersal starts around 10 August, peaks around 30 August and ends by 25 September, lasting about 45 d. Over time, annual pollen emissions exhibit significant fluctuations and a downward trend.
Climate change and pollution have intensified pollen allergies. We developed a pollen emissions...
Altmetrics
Final-revised paper
Preprint