[1] Wolf K L, Lam S T, Mckeen J K, et al. Urban trees and human health:A scoping review[J]. Journal of Environmental Research and Public Health, 2020, 17(12):4371-4401.
[2] 欧阳昱晖,张罗.花粉过敏的防御和治疗[J].中国耳鼻咽喉头颈外科, 2020, 27(4):177-179.
[3] 安羽三,欧阳昱晖.季节性过敏性鼻炎的研究现状[J].中国耳鼻咽喉头颈外科, 2020, 27(4):199-201.
[4] Awaya A, Kuroiwa Y. The relationship between annual airborne pollen levels and occurrence of all cancers, and lung, stomach, colorectal, pancreatic and breast cancers:A retrospective study from the National Registry Database of Cancer Incidence in Japan, 1975-2015[J]. International Journal of Environmental Research and Public Health, 2020, 17(11):3950.
[5] Stickley A, Sheng Ng C F, Konishi S, et al. Airborne pollen and suicide mortality in Tokyo, 2001-2011[J]. Environmental Research, 2017, 155:134-140.
[6] Cicco M E D, Ferrante G, Amato D, et al. Climate change and childhood respiratory health:A call to action for paediatricians[J]. Journal of Environmental Research and Public Health, 2020, 17(12):5344-5356.
[7] D'amato G, Chong-Neto H J, Monge Ortega O P, et al. The effects of climate change on respiratory allergy and asthma induced by pollen and mold allergens[J]. International Journal of Environmental Research and Public Health, 2020, 75(9):2219-2228.
[8] Martínez-Bracero M, Alcázar P, Díaz de la Guardia C, et al. Pollen calendars:a guide to common airborne pollen in Andalusia[J]. Aerobiologia, 2015, 31(4):549-557.
[9] Katotomichelakis M, Nikolaidis C, Makris M, et al. The clinical significance of the pollen calendar of the Western Thrace/northeast Greece region in allergic rhinitis[J]. International Forum of Allergy&Rhinology, 2015, 5(12):1156-1163.
[10] Stix E, Ferretti M L. Pollen calendars of three locations in Western Germany[J]. Atlas European Des Pollens Allergisants, 1974:85-94.
[11] Adams-Groom B, Ambelas Skjøth C, Selby K, et al. Regional calendars and seasonal statistics for the United Kingdom's main pollen allergens[J]. Allergy, 2020, 75(6):1492-1494.
[12] Camacho I, Caeiro E, Nunes C, et al. Airborne pollen calendar of Portugal:A 15-year survey (2002-2017)[J]. Allergologia et Immunopathologia, 2020, 48(2):194-201.
[13] Lo F, Bitz C M, Battisti D S, et al. Pollen calendars and maps of allergenic pollen in North America[J]. Aerobiologia, 2019, 35(4):613-633.
[14] Šikoparija B, Marko O, Panić M, et al. How to prepare a pollen calendar for forecasting daily pollen concentrations of Ambrosia, Betula and Poaceae?[J]. Aerobiologia, 2018, 34(2):203-217.
[15] Gehrig R, Maurer F, Schwierz C. Designing new automatically generated pollen calendars for the public in Switzerland[J]. Aerobiologia, 2018, 34(3):349-362.
[16] Shin J Y, Han M J, Cho C, et al. Allergenic pollen calendar in Korea based on probability distribution models and Up-to-Date observations[J]. Allergy Asthma and Immunology Research, 2020, 12(2):259-273.
[17] Kim I, Kwak M J, Lee J K, et al. Flowering phenology and characteristics of pollen aeroparticles of Quercus species in Korea[J]. Forests, 2020, 11(2):232.
[18] Sofiev M, Bergmann K C. Allergenic pollen:A review of the production, release, distribution and health impacts[M]. Dordrecht:Springer, 2013:161-187.
[19] Pfaar O, Bastl K, Berger U, et al. Defining pollen exposure times for clinical trials of allergen immunotherapy for pollen-induced rhinoconjunctivitis:An EAACI position paper[J]. Allergy, 2017, 72(5):713-722.
[20] Pfaar O, Karatzas K, Bastl K, et al. Pollen season is reflected on symptom load for grass and birch pollen-induced allergic rhinitis in different geographic areas:An EAACI task force report[J]. Allergy, 2020, 75(5):1099-1106.
[21] Cariñanos P, Casares-Porcel M, Quesada-Rubio J-M. Estimating the allergenic potential of urban green spaces:A case-study in Granada, Spain[J]. Landscape and Urban Planning. 2014, 123:134-144.
[22] Cariñanos P, Casares-Porcel M, Díaz de la G C, et al. Assessing allergenicity in urban parks:A nature-based solution to reduce the impact on public health[J]. Environmental Research, 2017, 155:219-227.
[23] Velasco-Jiménez M J, Alcázar P, Cariñanos P, et al. Allergenicity of the urban green areas in the city of Córdoba (Spain)[J]. Urban Forestry&Urban Greening, 2020, 49:126600.
[24] Li S S, Guo Y M, Williams G, et al. The association between ambient temperature and children's lung function in Baotou, China[J]. International Journal of Biometeorology, 2015, 59(7):791-798.
[25] He S, Mou Z, Peng L, et al. Impacts of meteorological and environmental factors on allergic rhinitis in children[J]. International Journal of Biometeorology, 2017, 61(5):797-806.
[26] Hu Y B, Xu Z W, Jiang F, et al. Relative impact of meteorological factors and air pollutants on childhood allergic diseases in Shanghai, China[J]. Science of the Total Environment, 2020, 706:135975.
[27] Ortega-Rosas C I, Meza-Figueroa D, Vidal-Solano J R, et al. Association of airborne particulate matter with pollen, fungal spores, and allergic symptoms in an arid urbanized area[J]. Environmental Geochemistry and Health, 2021, 43(5):1761-1782.
[28] Kilic M, Altunoglu M K, Akpınar S, et al. Relationship between airborne pollen and skin prick test results in Elazığ, Turkey[J]. Aerobiologia, 2019, 35(4):593-604.
[29] Guilbert A, Simons K, Hoebeke L, et al. Short-Term effect of pollen and spore exposure on allergy morbidity in the Brussels-Capital region[J]. EcoHealth, 2016, 13(2):303-315.
[30] Wang X Y, Ma T T, Wang X Y, et al. Prevalence of pol-len-induced allergic rhinitis with high pollen exposure in grasslands of northern China[J]. Allergy, 2018, 73(6):1232-1243.
[31] Guilbert A, Cox B, Bruffaerts N, et al. Relationships between aeroallergen levels and hospital admissions for asthma in the Brussels-Capital Region:A daily time series analysis[J]. Environmental Health, 2018, 17(1):35-47.
[32] Jones N R, Agnew M, Banic I, et al. Ragweed pollen and allergic symptoms in children:Results from a threeyear longitudinal study[J]. Science of the Total Environment, 2019, 683:240-248.
[33] Bédard A, Sofiev M, Arnavielhe S, et al. Interactions between air pollution and pollen season for rhinitis using mobile technology:A MASK-POLLAR study[J]. The Journal of Allergy and Clinical Immunology:In Practice, 2020, 8(3):1063-1073.e4.
[34] Silver J D, Spriggs K, Haberle S G, et al. Using crowdsourced allergic rhinitis symptom data to improve grass pollen forecasts and predict individual symptoms[J]. Science of the Total Environment, 2020, 720:137351.
[35] Navares R, Aznarte J L. Geographical imputation of missing poaceae pollen data via convolutional neural networks[J]. Atmosphere, 2019, 10(11):717-727.
[36] Damialis A, Häring F, Gökkaya M, et al. Human exposure to airborne pollen and relationships with symptoms and immune responses:Indoors versus outdoors, circadian patterns and meteorological effects in alpine and urban environments[J]. Science of the Total Environment, 2019, 653:190-199.
[37] Thien F, Beggs P J, Csutoros D, et al. The Melbourne epidemic thunderstorm asthma event 2016:An investigation of environmental triggers, effect on health services, and patient risk factors[J]. The Lancet Planetary Health, 2018, 2(6):e255-e263.
[38] Berger M, Bastl K, Bastl M, et al. Impact of air pollution on symptom severity during the birch, grass and ragweed pollen period in Vienna, Austria:Importance of O3 in 2010-2018[J]. Environmental Pollution, 2020, 263:114526.
[39] Ouyang Y, Xu Z, Fan E, et al. Effect of nitrogen dioxide and sulfur dioxide on viability and morphology of oak pollen[J]. International Forum of Allergy&Rhinology, 2016, 6(1):95-100.
[40] Celenk S. Detection of reactive allergens in long-distance transported pollen grains:Evidence from Ambrosia[J]. Atmospheric Environment, 2019, 209:212-219.
[41] Schinasi L H, Kenyon C C, Moore K, et al. Heavy precipitation and asthma exacerbation risk among children:A case-crossover study using electronic health records linked with geospatial data[J]. Environmental Research, 2020, 188:109714.
[42] Eguiluz-Gracia I, Mathioudakis A G, Bartel S, et al. The need for clean air:The way air pollution and climate change affect allergic rhinitis and asthma[J]. Allergy, 2020, 75(9):2170-2184.
[43] Berger U, Karatzas K, Jaeger S, et al. Personalized pollen-related symptom-forecast information services for allergic rhinitis patients in Europe[J]. Allergy, 2013, 68(8):963-965.
[44] Bousquet J, Schunemann H J, Fonseca J, et al. MACVIA-ARIA Sentinel NetworK for allergic rhinitis (MASK-rhinitis):The new generation guideline implementation[J]. Allergy, 2015, 70(11):1372-1392.
[45] Karatzas K, Voukantsis D, Jaeger S, et al. The patient's hay-fever diary:Three years of results from Germany[J]. Aerobiologia, 2014, 30(1):1-11.
[46] Silver J D, Spriggs K, Haberle S, et al. Crowd-sourced allergic rhinitis symptom data:The influence of environmental and demographic factors[J]. Science of the Total Environment, 2020, 705:135147.
[47] Setti L, Passarini F, De Gennaro G, et al. SARS-Cov-2RNA found on particulate matter of Bergamo in Northern Italy:First evidence[J]. Environmental Research, 2020, 188:109754.
[48] Morawska L, Cao J. Airborne transmission of SARSCoV-2:The world should face the reality[J]. Environment International, 2020, 139:105730.
[49] Dunker S, Hornick T, Szczepankiewicz G, et al. No SARS-CoV-2 detected in air samples (pollen and particulate matter) in Leipzig during the first spread[J]. Science of the Total Environment, 2021, 755:142881.
[50] Patella V, Delfino G, Florio G, et al. Management of the patient with allergic and immunological disorders in the pandemic COVID-19 era[J]. Clinical and Molecular Allergy, 2020, 18(1):18.
[51] Zhang J J, Dong X, Cao Y Y, et al. Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China[J]. Allergy, 2020, 75(7):1730-1741.
[52] Stjepanovic B, Svecnjak Z, Hrga I, et al. Seasonal variation of airborne ragweed (Ambrosia artemisiifolia L.) pollen in Zagreb, Croatia[J]. Aerobiologia, 2015, 31(4):525-535.
[53] Sabit M, Ramos J D, Alejandro G J, et al. Seasonal distribution of airborne pollen in Manila, Philippines, and the effect of meteorological factors to its daily concentrations[J]. Aerobiologia, 2016, 32(3):375-383.
[54] Toro A R, Córdova J A, Canales M, et al. Trends and threshold exceedances analysis of airborne pollen concentrations in Metropolitan Santiago Chile[J]. PLoS ONE, 2015, 10(5):e0123077.
[55] Hadj Hamda S, Ben Dhiab A, Galán C, et al. Pollen spectrum in Northern Tunis, Tunisia[J]. Aerobiologia, 2017, 33(2):243-251.
[56] Adeniyi T A, Adeonipekun P A, Olowokudejo J D. Annual records of airborne pollen of Poaceae in five areas in Lagos, Nigeria[J]. Grana, 2018, 57(4):284-291.
[57] Tahir A, Jean J, Buttner M, et al. Annual comparison of grass, tree, and weed pollen in Las Vegas from 2015-2018[J]. Journal of Allergy and Clinical Immunology, 2020, 145(Suppl 2):AB35.
[58] Gowrie M. Airborne pollen sampling on the Caribbean Island of Trinidad and Tobago, WI[J]. Aerobiologia, 2016, 32(2):347-352.
[59] Calderón-Ezquerro M C, Guerrero-Guerra C, MartínezLópez B, et al. First airborne pollen calendar for Mexico City and its relationship with bioclimatic factors[J]. Aerobiologia, 2016, 32(2):225-244.
[60] 张军,徐新,张增信,等.南京市空气中花粉特征及其与气象条件关系[J].气象与环境学报, 2009, 25(5):67-71.
[61] Xu J X, Zhang D S. Daily variations of airborne pollen in Beijing Olympic Park during August of three consecutive years and their relationships with meteorological factors[J]. Forestry Studies in China, 2011, 13(2):154-162.
[62] 黄建花,王幼芳,沈春琳,等.上海地区气传花粉的监测[J].华东师范大学学报(自然科学版), 2013, 2(2):56-62.
[63] 李英,李月丛,吕素青,等.石家庄市空气花粉散布规律及与气候因子的关系[J].生态学报, 2014, 34(6):1575-1586.
[64] 李挚,何海娟,孙国强,等.北京市区与过敏相关的气传花粉[J].基础医学与临床, 2015, 35(6):734-738.
[65] Li J, Li Y C, Zhang Z, et al. The dispersion characteristics of airborne pollen in the Shijiazhuang (China) urban area and its relationship with meteorological factors[J]. Aerobiologia, 2018, 34(1):89-104.
[66] 吕素青,李月从,许清海,等.陕西中部黄土高原地区空气花粉组成及其与气候因子的关系——以洛川县下黑木沟村为例[J].生态学报, 2012, 32(24):7654-7666.
[67] 李媛媛,张芸,倪健,等.新疆天山大气桦木花粉与气象因子的相关分析[J].科学通报, 2019, 64(18):1909-1921.
[68] 张雨辰,马春梅,方伊曼.大气花粉监测与传播研究进展[J].微体古生物学报, 2018, 35(2):92-102.
[69] Rahman A, Luo C X, Chen B S, et al. Regional and seasonal variation of airborne pollen and spores among the cities of South China[J]. Acta Ecologica Sinica, 2020, 40(4):283-295.
[70] 徐景先,李耀宁,张德山.空气花粉变化规律和预测预报研究进展[J].生态学报, 2009, 29(7):3854-3863.
[71] Fuhrmann C M, Sugg M M, Konrad C E. Airborne pollen characteristics and the influence of temperature and precipitation in Raleigh, North Carolina, USA (1999-2012)[J]. Aerobiologia, 2016, 32(4):683-696.
[72] Galán C, Alcázar P, Oteros J, et al. Airborne pollen trends in the Iberian Peninsula[J]. Science of the Total Environment, 2016, 550:53-59.
[73] Oduber F, Calvo A I, Blanco-Alegre C, et al. Links between recent trends in airborne pollen concentration, meteorological parameters and air pollutants[J]. Agricultural and Forest Meteorology, 2019, 264:16-26.
[74] Kubik-Komar A, Piotrowska-Weryszko K, WeryszkoChmielewska E, et al. A study on the spatial and temporal variability in airborne Betula pollen concentration in five cities in Poland using multivariate analyses[J]. Science of the Total Environment, 2019, 660:1070-1078.
[75] ZiskA L H, Makra L, Harry S K, et al. Temperature-related changes in airborne allergenic pollen abundance and seasonality across the northern hemisphere:A retrospective data analysis[J]. The Lancet Planetary Health, 2019, 3(3):e124-e131.
[76] Galán C, Thibaudon M. Climate change, airborne pollen, and pollution[J]. Allergy, 2020, 75(9):2354-2356.
[77] Türkmen Y, Çeter T, Pinar N M. Analysis of airborne pollen of Gümüşhane Province in northeastern Turkey and its relationship with meteorological parameters[J]. Turkish Journal of Botany, 2018, 42(6):687-700.
[78] Ruiz-Valenzuela L, Aguilera F. Trends in airborne pollen and pollen-season-related features of anemophilous species in Jaen (south Spain):A 23-year perspective[J]. Atmospheric Environment, 2018, 180:234-243.
[79] Bruffaerts N, De Smedt T, Delcloo A, et al. Comparative long-term trend analysis of daily weather conditions with daily pollen concentrations in Brussels, Belgium[J]. International Journal of Biometeorology, 2018, 62(3):483-491.
[80] Severova E, Volkova O. Variations and trends of Betula pollen seasons in Moscow (Russia) in relation to meteorological parameters[J]. Aerobiologia, 2017, 33(2):253-264.
[81] Velasco-JiméneZ M J, Alcázar P, Díaz de la Guardia C, et al. Pollen season trends in winter flowering trees in South Spain[J]. Aerobiologia, 2020, 36(2):213-224.
[82] Latorre F, Rotundo C, Abud Sierra M L, et al. Daily, seasonal, and interannual variability of airborne pollen of Araucaria angustifolia growing in the subtropical area of Argentina[J]. Aerobiologia, 2020, 36(2):277-290.
[83] Fang Y M, Ma C M, Bunting M J, et al. Airborne pollen concentration in Nanjing, Eastern China, and its relationship with meteorological factors[J]. Journal of Geophysical Research-Atmospheres, 2018, 123(19):10842-10856.
[84] Cristofolini F, Anelli P, Billi B M, et al. Temporal trends in airborne pollen seasonality:Evidence from the Italian POLLnet network data[J]. Aerobiologia, 2020, 36(1):63-70.
[85] Ojrzyńska H, Bilińska D, Werner M, et al. The influence of atmospheric circulation conditions on Betula and Alnus pollen concentrations in Wrocław, Poland[J]. Aerobiologia, 2020, 36(2):261-276.
[86] Paschalidou A K, Psistaki K, Charalampopoulos A, et al. Identifying patterns of airborne pollen distribution using a synoptic climatology approach[J]. Science of the Total Environment, 2020, 714:136625.
[87] Helfman-Hertzog I, Kutiel H, Levetin E, et al. The impact of Sharav weather conditions on airborne pollen in Jerusalem and Tel Aviv (Israel)[J]. Aerobiologia, 2018, 34(4):479-511.
[88] Ciani F, Marchi G, Dell'Olmo L, et al. Contribution of land cover and wind to the airborne pollen recorded in a South European urban area[J]. Aerobiologia, 2020, 36(3):325-340.
[89] Katz D S W, Batterman S A. Urban-scale variation in pollen concentrations:A single station is insufficient to characterize daily exposure[J]. Aerobiologia, 2020, 36(3):417-431.
[90] Monroy-Colín A, Silva-Palacios I, Tormo-Molina R, et al. Environmental analysis of airborne pollen occurrence, pollen source distribution and phenology of Fraxinus angustifolia[J]. Aerobiologia, 2018, 34(3):269-283.
[91] Fernández-Rodríguez S, Maya-Manzano J M, Colín A M, et al. Understanding hourly patterns of Olea pollen concentrations as tool for the environmental impact assessment[J]. Science of the Total Environment, 2020, 736:139363.
[92] Surek G, Mányoki G, Csonka B, et al. Studying correspondence of ragweed pollen's airborne concentration and the new greening measures under the common agriculture policy[J]. Mechanization in agriculture&Conserving of the resources, 2017, 63(3):115-118.
[93] Charalampopoulos A, Lazarina M, Tsiripidis I, et al. Quantifying the relationship between airborne pollen and vegetation in the urban environment[J]. Aerobiologia, 2018, 34(3):285-300.
[94] Rojo J, Oteros J, Pérez-Badia R, et al. Near-ground effect of height on pollen exposure[J]. Environmental Research, 2019, 174:160-169.
[95] Rojo J, Oteros J, Picornell A, et al. Land-Use and height of pollen sampling affect pollen exposure in Munich, Germany[J]. Atmosphere, 2020, 11(2):145.
[96] Šikoparija B, Mimić G, Panić M, et al. High temporal resolution of airborne Ambrosia pollen measurements above the source reveals emission characteristics[J]. Atmospheric Environment, 2018, 192:13-23.
[97] Fernández-Rodríguez S, Cortés-Pérez J P, Muriel P P, et al. Environmental impact assessment of Pinaceae airborne pollen and green infrastructure using BIM[J]. Automation in Construction, 2018, 96:494-507.
[98] Devadas R, Huete A R, Vicendese D, et al. Dynamic ecological observations from satellites inform aerobiology of allergenic grass pollen[J]. Science of the Total Environment, 2018, 633:441-451.
[99] Li X, Zhou Y, Meng L, et al. Characterizing the relationship between satellite phenology and pollen season:A case study of birch[J]. Remote Sensing of Environment, 2019, 222:267-274.
[100] Huete A, Tran N N, Nguyen H, et al. Forecasting pollen aerobiology with modis EVI, land cover, and phenology using machine learning tools[C]//IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium. Yokohama, Japan:IEEE, 2019:5429-5432.
[101] Weinberger K R, Kinney P L, Robinson G S, et al. Levels and determinants of tree pollen in New York City[J]. Journal of Exposure Science&Environmental Epi-demiology, 2018, 28(2):119-124.
[102] Kasprzyk I, Ćwik A, Kluska K, et al. Allergenic pollen concentrations in the air of urban parks in relation to their vegetation[J]. Urban Forestry&Urban Greening, 2019, 46:126486.
[103] Aaby B. NAP percentages as an expression of cleared areas[J]. Paläoklimaforschung, 1994, 12:13-27.
[104] Rojo J, Rapp A, Lara B, et al. Effect of land uses and wind direction on the contribution of local sources to airborne pollen[J]. Science of the Total Environment, 2015, 538:672-682.
[105] Maya-Manzano J M, Sadyś M, Tormo-Molina R, et al. Relationships between airborne pollen grains, wind direction and land cover using GIS and circular statistics[J]. Science of the Total Environment, 2017, 584-585:603-613.
[106] Kim K R, Han M J, Oh J-W. Forecast for pollen allergy:A review from field observation to modeling and services in Korea[J]. Immunology and Allergy Clinics of North America, 2021, 41(1):127-141.
[107] Kasprzyk I, Walanus A. Description of the main Poaceae pollen season using bi-Gaussian curves, and forecasting methods for the start and peak dates for this type of season in Rzeszów and Ostrowiec Sw.(SE Poland)[J]. Journal of Environmental Monitoring, 2010, 12(4):906-916.
[108] Silva-Palacios I, Fernández-Rodríguez S, Durán-Barroso P, et al. Temporal modelling and forecasting of the airborne pollen of Cupressaceae on the southwestern Iberian Peninsula[J]. International Journal of Biometeorology, 2016, 60(2):297-306.
[109] Kubik-Komar A, Piotrowska-Weryszko K, WeryszkoChmielewska E, et al. Analysis of Fraxinus pollen seasons and forecast models based on meteorological factors[J]. Annals of Agricultural and Environmental Medicine, 2018, 25(2):285-291.
[110] Ascari L, Siniscalco C, Palestini G, et al. Relationships between yield and pollen concentrations in Chilean hazelnut orchards[J]. European Journal of Agronomy, 2020, 115:126036.
[111] Ritenberga O, Sofiev M, Siljamo P, et al. A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe[J]. Science of the total Environment, 2018, 615:228-239.
[112] Picornell A, Oteros J, Trigo M M, et al. Increasing resolution of airborne pollen forecasting at a discrete sampled area in the southwest Mediterranean Basin[J]. Chemosphere, 2019, 234:668-681.
[113] Oteros J, Bergmann K C, Menzel A, et al. Spatial interpolation of current airborne pollen concentrations where no monitoring exists[J]. Atmospheric Environment, 2019, 199:435-442.
[114] García-Mozo H, Yaezel L, Oteros J, et al. Statistical approach to the analysis of olive long-term pollen season trends in southern Spain[J]. Science of the Total Environment, 2014, 473/474:103-109.
[115] Galera M D, Elvira-Rendueles B, Moreno J M, et al. Analysis of airborne Olea pollen in Cartagena (Spain)[J]. Science of the Total Environment, 2018, 622/623:436-445.
[116] Jochner-Oette S, Menzel A, Gehrig R, et al. Decrease or increase?Temporal changes in pollen concentrations assessed by Bayesian statistics[J]. Aerobiologia, 2019, 35(1):153-163.
[117] García-Mozo H, Oteros J A, Galán C. Impact of land cover changes and climate on the main airborne pollen types in Southern Spain[J]. Science of the Total Environment, 2016, 548/549:221-228.
[118] Rojo J, Rivero R, Romeromorte J, et al. Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing[J]. International Journal of Biometeorology, 2017, 61(2):335-348.
[119] Fernández-Rodríguez S. Regional forecast model for the Olea pollen season in Extremadura (SW Spain)[J]. International Journal of Biometeorology, 2016, 60(10):1509-1517.
[120] Lara B, Rojo J, Fernández-González F, et al. Prediction of airborne pollen concentrations for the plane tree as a tool for evaluating allergy risk in urban green areas[J]. Landscape and Urban Planning, 2019, 189:285-295.
[121] Zhang Y, Bielory L, Cai T, et al. Predicting onset and duration of airborne allergenic pollen season in the United States[J]. Atmospheric Environment, 2015, 103:297-306.
[122] Recio M, Picornell A, Trigo M M, et al. Intensity and temporality of airborne Quercus pollen in the southwest Mediterranean area:Correlation with meteorological and phenoclimatic variables, trends and possible adaptation to climate change[J]. Agricultural and Forest Meteorology, 2018, 250-251:308-318.
[123] Tseng Y T, Kawashima S, Kobayashi S, et al. Algorithm for forecasting the total amount of airborne birch pollen from meteorological conditions of previous years[J]. Agricultural and Forest Meteorology, 2018, 249:35-43.
[124] Katz D S W, Morris J R, Batterman S A. Pollen production for 13 urban North American tree species:Allometric equations for tree trunk diameter and crown area[J]. Aerobiologia, 2020, 36(3):401-415.
[125] Tseng Y T, Kawashima S. Applying a pollen forecast algorithm to the Swiss Alps clarifies the influence of topography on spatial representativeness of airborne pollen data[J]. Atmospheric Environment, 2019, 212:153-162.
[126] Cordero J M, Rojo J, Gutiérrez-Bustillo A M, et al. Predicting the Olea pollen concentration with a machine learning algorithm ensemble[J]. International Journal of Biometeorology, 2021, 65(4):541-554.
[127] Maya-Manzano J M, Smith M, Markey E, et al. Recent developments in monitoring and modelling airborne pollen, a review[J]. Grana, 2020:1-19.
[128] Nowosad J, Stach A, Kasprzyk I, et al. Statistical techniques for modeling of Corylus, Alnus, and Betula pollen concentration in the air[J]. Aerobiologia, 2018, 34(3):301-313.
[129] Bogawski P, Grewling Ł, Jackowiak B. Predicting the onset of Betula pendula flowering in Poznań(Poland) using remote sensing thermal data[J]. Science of the Total Environment, 2019, 658:1485-1499.
[130] Nowosad J. Spatiotemporal models for predicting high pollen concentration level of Corylus, Alnus, and Betula[J]. International Journal of Biometeorology, 2016, 60(6):843-855.
[131] 赵文芳,王京丽,尚敏,等.基于粒子群优化和支持向量机的花粉浓度预测模型[J].计算机应用, 2019, 39:98-104.
[132] Lops Y, Choi Y, Eslami E, et al. Real-time 7-day forecast of pollen counts using a deep convolutional neural network[J]. Neural Computing&Applications, 2020, 32(15):11827-11836.
[133] Seo Y A, Kim K R, Cho C, et al. Deep neural networkbased concentration model for Oak pollen allergy warning in South Korea[J]. Allergy Asthma and Immunology Research, 2020, 12(1):149-163.
[134] Valencia J A, Astray G, Fernández-González M, et al. Assessment of neural networks and time series analysis to forecast airborne Parietaria pollen presence in the Atlantic coastal regions[J]. International Journal of Biometeorology, 2019, 63(6):735-745.
[135] Navares R, Aznarte J L. Forecasting Plantago pollen:Improving feature selection through random forests, clustering, and Friedman tests[J]. Theoretical and Applied Climatology, 2020, 139(1/2):163-174.
[136] Astray G, Fernández-González M, Rodríguez-Rajo F J, et al. Airborne castanea pollen forecasting model for ecological and allergological implementation[J]. Science of the Total Environment, 2016, 548/549:110-121.
[137] Zewdie G K, Lary D, Levetin E, et al. Applying deep neural networks and ensemble machine learning methods to forecast airborne Ambrosia pollen[J]. International Journal of Environmental Research and Public Health, 2019, 16(11):1-14.
[138] Zewdie G K, Lary D J, Liu X, et al. Estimating the daily pollen concentration in the atmosphere using machine learning and NEXRAD weather radar data[J]. Environmental Monitoring and Assessment, 2019, 191(7):418-427.
[139] Zewdie G K, Liu X, Wu D, et al. Applying machine learning to forecast daily Ambrosia pollen using environmental and NEXRAD parameters[J]. Environmental Monitoring and Assessment, 2019, 191(2):261-272.
[140] Tseng Y-T, Kawashima S, Kobayashi S, et al. Forecasting the seasonal pollen index by using a hidden Markov model combining meteorological and biological factors[J]. Science of the Total Environment, 2020, 698:134246.
[141] Navares R, Aznarte J L. Deep learning architecture to predict daily hospital admissions[J]. Neural Computing&Applications, 2020, 32:16235-16244.
[142] Csépe Z, Leelőssy Á, Mányoki G, et al. The application of a neural network-based ragweed pollen forecast by the Ragweed Pollen Alarm System in the Pannonian biogeographical region[J]. Aerobiologia, 2020, 36(2):131-14.