承德北部空气负氧离子浓度特征及预报模型

Characteristics and Prediction Model of Air Negative Oxygen Ion Concentration in Northern Chengde

利用承德北部丰宁县2020年1月1日—2022年5月31日2个空气负氧离子站监测资料,以及同期的气象环境数据,分析负氧离子浓度时间变化特征、与气象环境要素的时序关系及关键影响因素,建立负氧离子浓度的预测模型。结果表明:丰宁城市公园、林区的负氧离子浓度年均值分别为1358.7、1955.8个/cm^(3),日平均最大值分别为3867、5845个/cm^(3),具有治疗和康复功效的自然环境条件;城市公园和林区的负氧离子浓度月变化均呈“单峰”型分布,峰值分别出现在7月(1889.5个/cm^(3))、8月(2516.3个/cm^(3)),最小值均出现在1月,林区各月浓度明显高于城市公园;负氧离子浓度日变化均呈“双峰”型,峰值分别出现在06时及20时前后,最小值出现在14时前后,夜间浓度均大于白天;城市公园、林区的负氧离子浓度与气温、降水量、相对湿度、风速、日照及PM_(2.5)、O_(3)浓度显著相关,城市公园受气象环境要素影响更大;利用多元回归方法,分别建立城市公园和林区的负氧离子浓度预报模型,2个模型的预报准确率>70%的占比分别为80.9%、73.7%,拟合效果良好。

Based on the Negative Oxygen Ion(NAI)concentration observation station data,meteorological data and environmental data from January 1st,2020 to May 31st,2022 in Fengning,the temporal variation characteristics of the NAI concentration and its temporal relationship with meteorological and environmental factors were analyzed in this paper,and key influencing factors that affected the NAI concentration were identified.A prediction model of NAI concentration was established.The results showed that the average annual concentrations of the NAI in the urban park and the forest region in Fengning were 1358.7 and 1995.8 ion·cm^(-3),respectively,with daily average maximum values of 3867 and 5845 ion·cm^(-3),indicating that there were natural environmental conditions for treatment and rehabilitation in the urban park and the forest region.The monthly variations of NAI concentration in the urban park and the forest region showed a single peak distribution,with peaks appearing in July(1889.5 ion·cm^(-3))and August(2516.3 ion·cm^(-3))respectively,and the minimum value in two regions appearing in January.The NAI concentration in the forest region was significantly higher than that in the urban park.The daily variation of NAI concentration showed a bimodal distribution,with peaks appearing around 06:00 and 20:00,respectively,and the minimum value appearing around 14:00.The concentrations at night in two regions were higher than that during the day.The air temperature,precipitation,relative humidity,wind speed,sunshine,PM_(2.5) and O_(3) were significantly correlated with NAI concentration in the urban park and the forest region.The meteorological and environmental factors affected urban park more than forest region.Two predictive models for the NAI concentrations in the urban park and the forest region were established using the multiple regression methods.The proportions of days with prediction accuracy greater than 70%for the two models were 80.9%and 73.7%,respectively,indicating that two predictive models had good fitting effects and could provide meteorological services for forest health and healthy life.