沧州市大气自净能力特征分析
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摘要
利用沧州1975—2018年逐日地面气象观测资料和2013—2018年环境监测资料,采用国标法计算并分析了沧州地区大气自净能力的时空变化特征,探讨了气象要素、污染物指数与大气自净能力之间的关系。结果表明:沧州大气自净能力年变化呈显著减小趋势,气候倾向率为1.05×10~4km~2·a~(-1)·(10a)~(-1),春季3—5月大气自净能力较强, 8月、11月、12月和1月较弱;风速、小风频率年变化与大气自净能力的相关性显著,相关系数分别为0.910、-0.807,风向出现频率与大气自净能力的相关性较差,降水日平均大气自净能力小于非降水日;O_3、CO和SO_2分指数与大气自净能力相关性较好,大气自净能力对区域空气质量变化具有指示意义。
The daily surface meteorological observation data in Cangzhou from 1975 to 2018 and the environmental monitoring data from 2013 to 2018 were applied. The spatial and temporal variation characteristics of atmospheric self-purification ability in Cangzhou area were calculated and analyzed using national standard method, and the relationship between meteorological elements, pollutant index and atmospheric self-purification ability was discussed. The results showed that the annual change of atmospheric self-purification capability in Cangzhou showed a significant decrease trend, and the climate trend rate was 1.05×10~4km~2·a~(-1)·(10 a)~(-1). The atmospheric self-purification capability was relatively strong from March to May, and was relatively weak in August, November, December and January. The annual variations of wind speed and small wind frequency had a significant correlation with atmospheric self-purification ability. The correlation coefficients were 0.910 and-0.807, respectively. The correlation between the occurrence frequency of wind direction and atmospheric self-purification ability was poor. The average atmospheric self-purification capability on precipitation days was smaller than that on non-precipitation days. The correlation between O_3, CO and SO_2 sub-indexes and atmospheric self-purification ability was good, and atmospheric self-purification ability was indicative of regional air quality change.
The daily surface meteorological observation data in Cangzhou from 1975 to 2018 and the environmental monitoring data from 2013 to 2018 were applied. The spatial and temporal variation characteristics of atmospheric self-purification ability in Cangzhou area were calculated and analyzed using national standard method, and the relationship between meteorological elements, pollutant index and atmospheric self-purification ability was discussed. The results showed that the annual change of atmospheric self-purification capability in Cangzhou showed a significant decrease trend, and the climate trend rate was 1.05×10~4km~2·a~(-1)·(10 a)~(-1). The atmospheric self-purification capability was relatively strong from March to May, and was relatively weak in August, November, December and January. The annual variations of wind speed and small wind frequency had a significant correlation with atmospheric self-purification ability. The correlation coefficients were 0.910 and-0.807, respectively. The correlation between the occurrence frequency of wind direction and atmospheric self-purification ability was poor. The average atmospheric self-purification capability on precipitation days was smaller than that on non-precipitation days. The correlation between O_3, CO and SO_2 sub-indexes and atmospheric self-purification ability was good, and atmospheric self-purification ability was indicative of regional air quality change.
引文
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[2]李崇,袁子鹏,吴宇童,等.沈阳一次严重污染天气过程持续和增强气象条件分析[J].环境科学研究,2017,30(3):349-358.
[3]杜吴鹏,房小怡,孟伟,等.气象因子对北京一次重污染天气过程影响研究[J].环境科学与技术,2016,39(8):123-128,153.
[4]Yang J,Duan K,Kang S,et al.Potential feedback between aerosols and meteorological conditions in a heavy pollution event over the Tibetan Plateau and Indo-Gangetic Plain[J].Climate Dynamics,2017,48(9-10):2901-2917.
[5]吴蒙,范绍佳,吴兑,等.广州地区灰霾与清洁天气变化特征及影响因素分析[J].中国环境科学,2012,32(8):1409-1415.
[6]周兆媛,张时煌,高庆先,等.京津冀地区气象要素对空气质量的影响及未来变化趋势分析[J].资源科学,2014,36(1):191-199.
[7]郝巨飞,张功文.邢台市大气稳定度和混合层厚度特征研究[J].气象科技,2016,44(1):118-122.
[8]叶堤,王飞,陈德蓉.重庆市多年大气混合层厚度变化特征及其对空气质量的影响分析[J].气象与环境学报,2008(4):41-44.
[9]张恒德,张碧辉,吕梦瑶,等.北京地区静稳天气综合指数的初步构建及其在环境气象中的应用[J].气象,2017,43(8):998-1004.
[10]大气自净能力等级:GB/T 34299-2017 [S].北京:中国标准出版社,2017.
[11]许启慧,范引琪,井元元,等.1972—2013年河北省大气环境容量的气候变化特征分析[J].高原气象,2017,36(6):1682-1692.
[12]郁珍艳,李正泉,高大伟,等.浙江省空气质量与大气自净能力的特征分析[J].气象,2017,43(3):323-332.
[13]董旭光,刘焕彬,汤子东,等.气候变化背景下山东大气自净能力特征分析[J].海洋气象学报,2018,38(4):93-102.
[14]朱蓉,张存杰,梅梅.大气自净能力指数的气候特征与应用研究[J].中国环境科学,2018,38(10):3601-3610.
[15]河北省天气预报手册编写组.河北省天气预报手册[M].北京:气象出版社,2017:23-24.
[16]彭思敏,李育,李依婵.全球季风区的定义与变化及其影响因素[J].亚热带资源与环境学报,2019,14(1):1-8.
[17]董继元,王式功,尚可政.降水对中国部分城市空气质量的影响分析[J].干旱区资源与环境,2009,23(12):43-48.
[18]王淑云,节江涛,熊险平,等.城市空气质量与气象条件的关系及空气质量预报系统[J].气象科技,2006(6):688-692.
[19]王明星.大气化学[M].北京:气象出版社,1999:125-162,183-185,330-332.
[20]宁志远.淄博市大气重污染过程污染来源及其与气象条件的关联性分析[D].山东:山东师范大学,2017:1-4.
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