机构地区:[1]川东北强天气研究南充市重点实验室,四川南充637000
出 处:《绿色科技》2023年第22期148-151,157,共5页Journal of Green Science and Technology
基 金:川东北强天气研究南充市重点实验室科技发展基金项目(编号:NCQXKJ202202)。
摘 要:为了解广元市空气污染物特征,研究空气污染情况与气象条件的关系,结合2017-2021年广元市环境空气质量自动监测数据和气象观测资料,从季、年角度分析了近5年来广元地区空气质量时空分布特征,综合运用相关性分析、多元线性回归等方法,建立了广元市污染物浓度预报模型,并进行验证。结果表明:2017-2021年广元市空气质量总体上较好,等级以优为主,空气“优”时段占比90%以上,在冬季空气污染时段首要污染物以PM_(2.5)为主,而夏季首要污染物以O_(3)为主,其他3种污染物CO、NO_(2)、SO_(2)的浓度都较小,对广元市空气质量几乎没有影响。空气质量指数呈季节性周期性变化,秋冬季节空气污染最严重,夏季空气质量最好。从地区来看,广元市五地中市区和青川空气质量最好,剑阁次之,苍溪和旺苍较差。O_(3)浓度与平均温度、最高温度、日照呈显著正相关,与相对湿度、降水量呈显著负相关;PM_(2.5)浓度与平均气温、最高气温、最低气温呈显著正相关,与气压呈较显著负相关,模型拟合度R^(2)均能达到0.8;PM_(10)与气压呈显著正相关,与降水量呈较显著正相关,与最低气温和风速呈较显著负相关。预测模型较为准确地预测了未来空气污染物浓度,模型拟合度R^(2)可以达到0.7~0.8,表明了该模型能够满足日常业务需求。可为广元市大气污染防治攻坚战提供科学决策依据。In order to understand the characteristics of air pollutants in Guangyuan and study the relationship between air pollution and meteorological conditions,the aim is to provide a scientific basis for decision-making in the battle against air pollution in Guangyuan City.Based on the air quality automatic monitoring data and meteorological observations from 2017 to 2021 and the spatial and temporal distribution of air quality in Guangyuan City,the past five years was analyzed from a quarterly and annual perspective.Using a combination of correlation analysis and multiple linear regression,a prediction model for pollutant concentrations in Guangyuan was developed and validated.The results showed that Guangyuan's air quality from 2017 to 2021 was generally good,with the summer of"excellent"air accounting for more than 90%of the time.PM_(2.5)was the main pollutant during the winter air pollution period.In summer,O_(3)was the main pollutant,and the concentrations of CO,NO_(2)and SO_(2)were lower,which had little effect on Guangyuan's air quality.The air quality index(AQI)changes seasonally and periodically.The air pollution is most serious in autumn and winter,and the air quality is best in summer.Regionally urban areas in Guangyuan and Qingchuan County have the best air quality,followed by Jiange,Cangxi County and Wangcang County.O_(3)concentration was positively correlated with mean temperature,maximum temperature and sunshine,and negatively correlated with relative humidity and precipitation;The concentration of PM_(2.5)was positively correlated with mean temperature,maximum temperature and minimum temperature,and negatively correlated with air pressure.The fitting degree of the model was 0.8;PM_(10)was positively correlated with air pressure,positively correlated with precipitation,and negatively correlated with minimum temperature and wind speed.The prediction model can accurately predict the future air pollutant concentration,and the model fitting degree R^(2)can reach 0.7 to 0.8,indicating that the model can meet
分 类 号:X511[环境科学与工程—环境工程]
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