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.