Prediction Model for Annual Variation in Total Pollen by Allergenic Trees in Korean Cities.

PURPOSE: Pollen forecasting systems can provide information for coping with respiratory allergies. They estimate daily pollen production, dispersal, deposition, and removal based on daily weather conditions to predict daily pollen concentrations and provide allergy warnings. As of 2023, the Korea Meteorological Administration (KMA) provides 2-day forecast of allergenic pollens. However, unlike these models, long-term analysis of annual observations of tree pollen reveal annual variations. Therefore, in this study, we aimed to develop annual prediction models for allergenic tree pollens based on long-term multi-site pollen and meteorological data. METHODS: Daily pollen concentrations were observed using Hirst-type volumetric spore traps at nine sites in Korea from 1998 to 2021, and daily weather data from the closest KMA stations were utilized. Models were developed to predict the seasonal pollen integral of seven tree species based on monthly mean temperature, wind speed, and total precipitation using three variable selection methods: 1) the t-test based key variable screening followed by linear regression with stepwise procedure (TM), 2) direct linear regression with stepwise procedure from the full variable model (FM), and 3) LASSO regression from the full variable model (LM). RESULTS: Data obtained during 1998-2017 and 2018=2021 were utilized for model development and validation, respectively. The root mean squared error, mean absolute error, mean error, and coefficient of determination (R²) revealed that the TM models were best suited for actual forecasting, even though R² in the TM model was lower than those of the FM and LM models. CONCLUSIONS: The annual variation model in this study can be integrated with the daily pollen forecast model by controlling the annual pollen potential, and the accuracy of the daily forecast can be improved accordingly.

Annual Change in Fungal Concentrations and Allergic Sensitization Rates to Alternaria and Cladosporium in Korea During the Period 1998-2022.

PURPOSE: Atmospheric fungi are associated with respiratory allergies in humans, and some fungal spores can cause allergic diseases. Environmental and biological factors influence the concentrations of atmospheric spores. In this study, we evaluated the climate change-induced annual variations in fungal spore concentrations and allergic sensitization rates in the Seoul Metropolitan Area over a period of 25 years. METHODS: Fungal spores and pollen were obtained from Hanyang University Seoul and Guri Hospitals; they were identified and counted for 25 years (1998-2022). The study participants included patients who underwent tests for allergic diseases in both hospitals. Their allergenic sensitization rates were determined via allergic skin prick and serum tests, after which their sensitization rates to allergenic fungi and pollens were calculated. The daily climatic variables were obtained from the Korea Meteorological Administration. RESULTS: The total annual atmospheric fungal concentrations decreased in both areas during the period. Simultaneously, we recruited 21,394 patients with allergies (asthma, 1,550; allergic rhinitis, 5,983; and atopic dermatitis, 5,422) from Seoul and Guri Hospitals for allergenic fungal sensitization evaluations over the period. The allergenic fungal sensitization rates decreased annually in both areas over that time `+(Alternaria [3.5%] and Cladosporium [4.4%] in 1998; Alternaria [0.2%] and Cladosporium [0.2%] in 2022). In contrast, the annual pollen concentrations increased with the sensitization rates to pollen in children. CONCLUSIONS: The atmospheric fungal concentrations decreased annually, with allergic sensitization rate decreasing over the period of 25 years. Allergenic fungal sporulation could decrease with climate changes, such as desertification and drought. Extended monitoring periods and further large-scale studies are required to confirm the causality and to evaluate the impact of climate change.

Erratum: Analysis of the Association Among Air Pollutants, Allergenic Pollen, and Respiratory Virus Infection of Children in Guri, Korea During Recent 5 Years.

This corrects the article on p. 289 in vol. 14, PMID: 35557494.

Analysis of the Association Among Air Pollutants, Allergenic Pollen, and Respiratory Virus Infection of Children in Guri, Korea During Recent 5 Years.

PURPOSE: Concerns about the spread of infectious diseases have increased due to the coronavirus disease pandemic. Knowing the factors that exacerbate or increase the contagiousness of a virus could be a key to pandemic prevention. Therefore, we investigated whether the pandemic potential of infectious diseases correlates with the concentration of atmospheric substances. We also investigated whether environmental deterioration causes an increase in viral infections. METHODS: Pediatric patients (0-18 years old; n = 6,223) were recruited from those hospitalized for aggravated respiratory symptoms at Hanyang University Guri Hospital between January 1, 2015 and December 31, 2019. The number of viral infections was defined as the total number of virus-infected patients hospitalized for respiratory symptoms. We analyzed the association between the number of viral infections/week and the average concentrations of atmospheric substances including particulate matter (PM)10, PM2.5, O3, NO2, CO, SO2, and allergenic pollen) for that week. The cross-correlation coefficient between the weekly measures of pollens and viral infections was checked to determine which time point had the most influence. The association of atmospheric substances in that time, with the number of viral infections/week was investigated using multiple linear regression analysis to identify factors with the greatest influence. RESULTS: In spring the tree pollen average concentration one week earlier (t-1) had the greatest correlation with the average virus infection of a given week (t) (ρXY (h) =0.5210). The number of viral infections showed a statistically significant correlation with especially tree pollen concentration of 1 week prior (adj R²=0.2280). O3 concentration was correlated to the number of viral infections within that week (adj R²=0.2552) in spring, and weed pollen and CO concentration correlated (adj R²=0.1327) in autumn. CONCLUSIONS: Seasonal co-exposure to air pollutants and allergenic pollens may enhance respiratory viral infection susceptibility in children. Therefore, reducing the concentrations of air pollutants and pollens may help prevent future epidemics.

High-resolution wind speed forecast system coupling numerical weather prediction and machine learning for agricultural studies - a case study from South Korea.

Forecasting wind speed near the surface with high-spatial resolution is beneficial in agricultural management. There is a discrepancy between the wind speed information required for agricultural management and that produced by weather agencies. To improve crop yield and increase farmers' incomes, wind speed prediction systems must be developed that are customized for agricultural needs. The current study developed a high-resolution wind speed forecast system for agricultural purposes in South Korea. The system produces a wind speed forecast at 3 m aboveground with 100-m spatial resolution across South Korea. Logarithmic wind profile, power law, random forests, support vector regression, and extreme learning machine were tested as candidate methods for the downscaling wind speed data. The wind speed forecast system developed in this study provides good performance, particularly in inland areas. The machine learning-based methods give the better performance than traditional methods for downscaling wind speed data. Overall, the random forests are considered the best downscaling method in this study. Root mean square error and mean absolute error of wind speed prediction for 48 h using random forests are approximately 0.8 m/s and 0.5 m/s, respectively.

Determination of thermal sensation levels for Koreans based on perceived temperature and climate chamber experiments with hot and humid settings.

People perceive thermal sensation differently despite the same temperature value of thermal comfort index depending on various factors such as climate, culture, and physiological characteristics. The use of the thermal comfort index without optimization may lead to biases in assessment of thermal stress and sensation. This study aims to derive the perceived temperature (PT) ranges of thermal sensation levels related to heat stress for Koreans. The experiments were designed using a controlled environmental chamber to derive the PT ranges and were performed with subjects who are residents of Seoul, South Korea. The experiments were carried out in the summers of 2017 and 2018, and the thermal sensation votes were surveyed from 19 subjects whose mean age, height, weight, and body mass index were 22.5 years, 171 cm, 72 kg, and 23 kg⋅m-2, respectively. The derived PT ranges for Koreans led to a better performance than the reference PT ranges for Germans based on the results of validation. The thresholds of 'Warm,' 'Hot,' and 'Very hot' thermal sensation classes for Koreans were 28 °C, 36 °C, and 43 °C, respectively: higher than those for Germans. The results indicate that Koreans may have higher heat resistance or lower heat sensitivity than Germans.

Outdoor thermal stress changes in South Korea: Increasing inter-annual variability induced by different trends of heat and cold stresses.

Changes of thermal environment can lead to unfavorable impacts such as a decrease of thermal stratification, increase of energy consumption, and increase of thermal health risk. Investigating changes in outdoor thermal environments can provide meaningful information for addressing economic and social issues and related challenges. In this study, thermal environment changes in South Korea were investigated using a nonstationary two-component Gaussian mixture model (NSGMM) for air temperature and two thermal comfort indices. For this, the perceived temperature (PT) and universal thermal climate index (UTCI) were employed as the thermal comfort index. Thermal comfort indices were computed using observed meteorological data at 26 weather stations for 37 years in South Korea. Meanwhile, trends of thermal comforts in the warm and cool seasons were simultaneously modeled by the NSGMM. The results indicate significant increasing trends in thermal comfort indices for South Korea. The increasing trends in thermal comfort indices both the warm and cool seasons were detected while the magnitudes of the trends are significantly different. This difference between the magnitude of trends led to an increase in mean and inter-annual variability of thermal comfort indices based on PT, while an increase of mean and decrease of inter-annual variability were observed based on the UTCI. Moreover, the annual proportion of the category referring to days in comfort based on the results of PT has decreased due to the different trends of thermal comfort indices in the warm and cool seasons. This decrease may lead to an increase of thermal health risk that is larger than what would be expected from the results considering the increasing trend of the annual mean temperature in South Korea. From this result, it can be inferred that the thermal health risk in South Korea may be more adverse than what we originally expected from the current temperature trend.

Increased sensitization rates to tree pollens in allergic children and adolescents and a change in the pollen season in the metropolitan area of Seoul, Korea.

INTRODUCTION: Children with allergies are at greater risk of becoming sensitized to allergenic pollens in response to environmental changes. This study investigated the relationship between changes in pollination associated with meteorologic changes and the sensitization rates of children to tree pollen allergens in the metropolitan area of Seoul, Korea. METHODS: The study population consisted of 8,295 children who visited the pediatric allergy clinics at Hanyang University Seoul and Guri Hospital for allergy symptoms between January 1, 1998, and December 31, 2019. Pollen was collected at the two hospitals during the study using a Burkard 7-day sampler. Meteorologic data were obtained from the National Weather Service. RESULTS: Among the major tree pollens, the largest increase in allergic sensitization was to oak, hazel, and alder pollens (0.28% annually). The pollen-sensitization rates increased annually within younger age groups. The duration of the pollen season was 98 days in 1998 and 140 days in 2019. Positive correlations were determined between the duration of the pollen season and the rates of sensitization to tree pollens, as well as between the pollen-sensitization rates and increasing temperature. CONCLUSIONS: This study demonstrated the correlation between weather changes and the resulting changes in the pollen season with sensitization rates to allergenic pollens in children living in the Seoul metropolitan area. An annual increase in sensitization rates in younger children was determined. This pattern is expected to continue due to continuing climate change.

Forecast for Pollen Allergy: A Review from Field Observation to Modeling and Services in Korea.

Pollen, a major causal agent of respiratory allergy, is mainly affected by weather conditions. In Korea, pollen and weather data are collected by the national observation network. Forecast models and operational services are developed and provided based on the national pollen data base. Using the pollen risk forecast information will help patients with respiratory allergy to improve their lives. Changes in temperature and CO2 concentration by climate change affect the growth of plants and their capacity of producing more allergenic pollens, which should be considered in making the future strategy on treating allergy patients.

Erratum: Allergenic Pollen Calendar in Korea Based on Probability Distribution Models and Up-to-Date Observations.

This corrects the article on p. 259 in vol. 12, PMID: 32009321.

Intensity-duration-frequency relationship of WBGT extremes using regional frequency analysis in South Korea.

The risk levels of heat-related extreme events need to be estimated for prediction and real-time monitoring to mitigate their impacts on air quality, public health, the ecosystem, and critical infrastructure. Many countries have adopted meteorological variable base thresholds for assessing the risk level of heat-related extreme events. These thresholds provide an approximate risk level for a specific event but do not consider its intensity and duration in the risk assessment. The current study provides a statistical tool to assess the risk of heat-related extreme events while concurrently considering their intensities and durations based on the wet-bulb globe temperature (WBGT). To this end, the intensity-duration-frequency (IDF) relationship of the extreme WBGT in South Korea was derived. Regional frequency analysis was employed to understand the IDF relationship. Return levels of heat-related extreme events in South Korea were calculated and their characteristics were investigated based on the annual maximum WBGT observations. The results showed that the IDF relationship could provide the risks of heat-related extreme events while concurrently considering their intensities and durations. The extreme WBGT in South Korea was used to categorize two regions such as coastal and inland based on their statistical characteristics. The return levels of the annual maximum WBGT events were found to vary largely by location. The return levels corresponding to 32 °C with 3-h duration for stations in the coastal and inland regions ranged from 1- to 100-years and 3- to 1000-years, respectively. Mean values of return levels for heatwave events in Seoul, Incheon, Daejon, Gwangju, Daegu, and Busan were 2.8-, 8.4-, 15.3-, 2.8-, 1.6-, and 2.2-years, respectively. The return levels of heatwaves for the warmer cities are smaller than those for cooler cities. The return levels of the heatwave events in South Korea showed a significant increasing trend in several cities, supporting the notion that the impact of heatwave events on South Korea might become more severe in the future.

Event-Based Heat-Related Risk Assessment Model for South Korea Using Maximum Perceived Temperature, Wet-Bulb Globe Temperature, and Air Temperature Data.

This study aimed to assess the heat-related risk (excess mortality rate) at six cities, namely, Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan, in South Korea using the daily maximum perceived temperature (PTmax), which is a physiology-based thermal comfort index, the wet-bulb globe temperature, which is meteorology-based thermal comfort index, and air temperature. Particularly, the applicability of PTmax was evaluated using excess mortality rate modeling. An event-based heat-related risk assessment model was employed for modeling the excess mortality rate. The performances of excess mortality rate models using those variables were evaluated for two data sets that were used (training data, 2000-2016) and not used (test data, 2017-2018) for the construction of the assessment models. Additionally, the excess mortality rate was separately modeled depending on regions and ages. PTmax is a good temperature indicator that can be used to model the excess mortality rate in South Korea. The application of PTmax in modeling the total mortality rate yields the best performances for the test data set, particularly for young people. From a forecasting perspective, PTmax is the most appropriate temperature indicator for assessing the heat-related excess mortality rate in South Korea.

A simple high-resolution heat-stress forecast for Seoul, Korea: coupling climate information with an operational numerical weather prediction model.

To provide a simple high-resolution heat-stress forecast for Seoul, Korea, we coupled a high-resolution climate simulation (25 m grid spacing) for an average heat day with the operational forecasting model (5 km grid spacing). Thereby, we accounted for the meso-scale weather conditions and local-scale air temperature induced by land cover and the urban heat island effect. Moreover, we estimated the impacts of heat events using heat-related mortality rate. Applying the simple high-resolution heat-stress forecast for July and August 2016, we detected a substantial spatial variability in maximum air temperature and heat-related mortality rate in Seoul. The evaluation of simulated maximum air temperature compared to observations revealed a small deviation (MB = 0.11 K, RMSD = 1.40 K). Despite the limitation of using average conditions, it was an efficient way to identify particularly affected areas, neighbourhoods, and districts for releasing more location-specific heat-stress warnings.

Allergenic Pollen Calendar in Korea Based on Probability Distribution Models and Up-to-Date Observations.

PURPOSE: The pollen calendar is the simplest forecasting method for pollen concentrations. As pollen concentrations are liable to seasonal variations due to alterations in climate and land-use, it is necessary to update the pollen calendar using recent data. To attenuate the impact of considerable temporal and spatial variability in pollen concentrations on the pollen calendar, it is essential to employ a new methodology for its creation. METHODS: A pollen calendar was produced in Korea using data from recent observations, and a new method for creating the calendar was proposed, considering both risk levels and temporal resolution of pollen concentrations. A probability distribution was used for smoothing concentrations and determining risk levels. Airborne pollen grains were collected between 2007 and 2017 at 8 stations; 13 allergenic pollens, including those of alder, Japanese cedar, birch, hazelnut, oak, elm, pine, ginkgo, chestnut, grasses, ragweed, mugwort and Japanese hop, were identified from the collected grains. RESULTS: The concentrations of each pollen depend on locations and seasons due to large variability in species distribution and their environmental condition. In the descending order of concentration, pine, oak and Japanese hop pollens were found to be the most common in Korea. The pollen concentrations were high in spring and autumn, and those of oak and Japanese hop were probably the most common cause of allergy symptoms in spring and autumn, respectively. High Japanese cedar pollen counts were observed in Jeju, while moderate concentrations were in Jeonju, Gwangju and Busan. CONCLUSIONS: A new methodology for the creation of a pollen calendar was developed to attenuate the impact of large temporal and spatial variability in pollen concentrations. This revised calendar should be available to the public and allergic patients to prevent aggravation of pollen allergy.

Deep Neural Network-Based Concentration Model for Oak Pollen Allergy Warning in South Korea.

PURPOSE: Oak is the dominant tree species in Korea. Oak pollen has the highest sensitivity rate among all allergenic tree species in Korea. A deep neural network (DNN)-based estimation model was developed to determine the concentration of oak pollen and overcome the shortcomings of conventional regression models. METHODS: The DNN model proposed in this study utilized weather factors as the input and provided pollen concentrations as the output. Weather and pollen concentration data were used from 2007 to 2016 obtained from the Korea Meteorological Administration pollen observation network. Because it is difficult to prevent over-fitting and underestimation by using a DNN model alone, we developed a bootstrap aggregating-type ensemble model. Each of the 30 ensemble members was trained with random sampling at a fixed rate according to the pollen risk grade. To verify the effectiveness of the proposed model, we compared its performance with those of models of regression and support vector regression (SVR) under the same conditions, with respect to the prediction of pollen concentrations, risk levels, and season length. RESULTS: The mean absolute percentage error in the estimated pollen concentrations was 11.18%, 10.37%, and 5.04% for the regression, SVR and DNN models, respectively. The start of the pollen season was estimated to be 20, 22, and 6 days earlier than that predicted by the regression, SVR and DNN models, respectively. Similarly, the end of the pollen season was estimated to be 33, 20, and 9 days later that predicted by the regression, SVR and DNN models, respectively. CONCLUSIONS: Overall, the DNN model performed better than the other models. However, the prediction of peak pollen concentrations needs improvement. Improved observation quality with optimization of the DNN model will resolve this issue.

Quantification and evaluation of intra-urban heat-stress variability in Seoul, Korea.

This study quantifies heat-stress hazard (air temperature), vulnerability (heat vulnerability index and age score), and risk (heat-related mortality) on the district scale in Seoul, Korea, for a comprehensive heat-stress impact assessment. Moreover, the heat-stress impact assessment is evaluated by checking the spatial consistency between heat-stress hazard, vulnerability, and risk, which was rarely done before. We applied numerical and geo-empirical models to simulate the spatial pattern of heat-stress hazard. For heat-stress vulnerability, we used demographic and socioeconomic factors. Heat-related mortality was estimated based on an event-based heat-stress risk analysis. Results are that heat-stress hazard, vulnerability, and risk are spatially variable in Seoul. The highest heat-stress hazard was detected in the districts Mapo, Yeongdeungpo, and Yangcheon, the highest vulnerability in Jongno and the highest risk in Jongno and Yangcheon. The different components (heat-stress hazard, vulnerability, and risk) and variables (heat vulnerability index and percentage of seniors) showed different spatial patterns. Knowledge about the causes of higher heat-stress risk, either the hazard or vulnerability, is helpful to design tailored adaptation measures that focus on the reduction of thermal loads or on the preparation of the vulnerable population. The evaluation showed that heat-stress vulnerability and hazard explain the spatial pattern of risk only partly. This highlights the need to evaluate heat-stress impact assessment systems to produce reliable urban heat-stress maps.

Does the increase in ambient CO2 concentration elevate allergy risks posed by oak pollen?

Oak pollen is a major respiratory allergen in Korea, and the distribution of oak trees is expected to increase by ecological succession and climate change. One of the drivers of climate change is increasing CO2, which is also known to amplify the allergy risk of weed pollen by inducing elevated allergenic protein content. However, the impact of CO2 concentration on tree pollen is not clearly understood due to the experimental difficulties in carrying out extended CO2 treatment. To study the response of pollen production of sawtooth oak trees (Quercus acutissima) to elevated levels of ambient CO2, three open-top chambers at the National Institute of Forest Science in Suwon, Korea were utilized with daytime (8 am-6 pm) CO2 concentrations of ambient (× 1.0, ~ 400 ppm), × 1.4 (~ 560 ppm), and × 1.8 (~ 720 ppm) treatments. Each chamber had three sawtooth oak trees planted in September 2009. One or two trees per chamber matured to bloom in 2016. Five to six catkins were selected per tree and polyethylene bags were attached to collect pollen grains. The total number of catkins per tree was counted and the number and weight of pollen grains per catkin were measured. Oak allergen-Que a 1 (Allergon Co., Uppsala, Sweden)-was extracted and purified to make an ELISA kit by which the antigen levels in the pollen samples were quantified. Total pollen counts per tree of the × 1.4 and × 1.8 treatments showed significant increase of 353 and 1299%, respectively, from the × 1.0 treatment (p < 0.001). Allergenic protein contents at the × 1.4 and × 1.8 treatments also showed significant increase of 12 and 11%, respectively (p = 0.011). The × 1.8 treatment induced significant difference from the × 1.0 treatment in terms of pollen production and allergenic protein content, whereas the × 1.4 treatment showed mixed significance. In summary, the oak trees under the elevated CO2 levels, which are expected in the changing climate, produced significantly higher amount of pollen and allergenic protein than under the present air conditions.

Chamber and Field Studies demonstrate Differential Amb a 1 Contents in Common Ragweed Depending on CO2 Levels.

Although atmospheric carbon dioxide (CO2) has no apparent direct effect on human health, it does have direct effects on plants. The present study evaluated the influence of increased CO2 levels on the concentration of allergens from common ragweed pollen by setting up a chamber study to model future air conditions and a field study to evaluate current air conditions. For the chamber study, we established 20 ragweed plants in an open-top chamber under different CO2 levels (380-400, 500-520, 600-620, and 1,000-1,100 parts per million [ppm]). For the field study, we established ragweed plants in rural (Pocheon, Gyeonggi-do; mean CO2 320±54.8 ppm) and urban (Gangnam, Seoul; mean CO2 440±78.5 ppm) locations. Seeds of the common ragweed (Ambrosia artemisiifolia) were obtained from Daejin University. The Amb a 1 protein content of pollen extracts was quantified using a double sandwich enzyme-linked immunosorbent assay. In our chamber study, the median concentration of Amb a 1 in pollen increased with increasing in CO2 concentration (1.88 ng/µg in 380-400 ppm CO2; 3.14 ng/µg in 500-520 ppm CO2; 4.44 ng/µg in 600-620 ppm CO2; and 5.36 ng/µg in 1,000-1,100 ppm CO2). In our field study, we found no significantly different concentration of Amb a 1 between the pollen extracts at the Pocheon (mean±standard deviation, 1.63±0.3 ng/µg pollen in 320±54.8 ppm CO2) and the Gangnam (2.04±0.7 ng/µg pollen in CO2 in 440±78.5 ppm CO2) locations, although the concentration of Amb a 1 was increased in the Gangnam than in the Pocheon locations. Our results suggest that future increases in CO2 levels to more than 600 ppm will significantly elevate the Amb a 1 content in common ragweeds, although the current different CO2 levels do not cause differences in the Amb a 1 content of ragweed pollen.

Effects of heat waves on daily excess mortality in 14 Korean cities during the past 20 years (1991-2010): an application of the spatial synoptic classification approach.

The aims of this study are to explore the "offensive" summer weather types classified under the spatial synoptic classification (SSC) system and to evaluate their impacts on excess mortality in 14 Korean cities. All-cause deaths per day for the entire population were examined over the summer months (May-September) of 1991-2010. Daily deaths were standardized to account for long-term trends of subcycles (annual, seasonal, and weekly) at the mid-latitudes. In addition, a mortality prediction model was constructed through multiple stepwise regression to develop a heat-health warning system based on synoptic climatology. The result showed that dry tropical (DT) days during early summer caused excess mortality due to non-acclimatization by inhabitants, and moist tropical (MT) plus and double plus resulted in greater spikes of excess mortality due to extremely hot and humid conditions. Among the 14 Korean cities, highly excess mortality for the elderly was observed in Incheon (23.2%, 95%CI 5.6), Seoul (15.8%, 95%CI 2.6), and Jeonju (15.8%, 95%CI 4.6). No time lag effect was observed, and excess mortality gradually increased with time and hot weather simultaneously. The model showed weak performance as its predictions were underestimated for the validation period (2011-2015). Nevertheless, the results clearly revealed the efficiency of relative and multiple-variable approaches better than absolute and single-variable approaches. The results indicate the potential of the SSC as a suitable system for investigating heat vulnerability in South Korea, where hot summers could be a significant risk factor.

A biology-driven receptor model for daily pollen allergy risk in Korea based on Weibull probability density function.

Pollen is an important cause of respiratory allergic reactions. As individual sanitation has improved, allergy risk has increased, and this trend is expected to continue due to climate change. Atmospheric pollen concentration is highly influenced by weather conditions. Regression analysis and modeling of the relationships between airborne pollen concentrations and weather conditions were performed to analyze and forecast pollen conditions. Traditionally, daily pollen concentration has been estimated using regression models that describe the relationships between observed pollen concentrations and weather conditions. These models were able to forecast daily concentrations at the sites of observation, but lacked broader spatial applicability beyond those sites. To overcome this limitation, an integrated modeling scheme was developed that is designed to represent the underlying processes of pollen production and distribution. A maximum potential for airborne pollen is first determined using the Weibull probability density function. Then, daily pollen concentration is estimated using multiple regression models. Daily risk grade levels are determined based on the risk criteria used in Korea. The mean percentages of agreement between the observed and estimated levels were 81.4-88.2 % and 92.5-98.5 % for oak and Japanese hop pollens, respectively. The new models estimated daily pollen risk more accurately than the original statistical models because of the newly integrated biological response curves. Although they overestimated seasonal mean concentration, they did not simulate all of the peak concentrations. This issue would be resolved by adding more variables that affect the prevalence and internal maturity of pollens.