冬季不同植物群落对大气颗粒物浓度的阻滞作用
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X513

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国家自然科学基金(31600579);河南省科技攻关计划(202102110234);河南省高等学校重点研究项目(21A220003)


Blocking effects of plant communities on atmospheric particles in winter
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    摘要:

    为探讨不同植物群落对大气颗粒物浓度的影响,以郑州市金水区为例,在2020年冬季(2020年12月—2021年2月)对园林绿化区(数码公园)、居住区(正弘·蓝堡湾)、文教区(河南农业大学)内植物群落的PM2.5和PM10质量浓度及气象因子(温度、相对湿度和风速)进行监测.结果表明:每个功能区中不同样地之间的PM2.5、PM10质量浓度日变化趋势基本一致,一般为早高晚低;不同植物群落之间PM2.5和PM10质量浓度存在显著差异性,其中广场样地与其他样地的差异性最显著;3个功能区中各样地对PM2.5和PM10质量浓度的阻滞率均表现为乔灌草结构最高,乔灌结构和乔草结构次之,且多表现为乔灌样地大于乔草样地,灌草结构和草坪最低;研究区域PM2.5、PM10质量浓度与温度呈负相关,与相对湿度呈正相关,与风速呈负相关.

    Abstract:

    To explore the blocking impact of plant communities on atmospheric particulate matters,we monitored the PM2.5 and PM10 concentrations and related meteorological factors near plant communities in three functional areas of Zhengzhou's Jinshui district,which were garden area (Digital Park),residential area (Zhengzhou Blue Bay),and cultural & educational area (Henan Agricultural University).The monitoring period covered a whole winter from December 2020 to February 2021.The results indicated that the diurnal variation trends of PM2.5 and PM10 concentrations were basically the same for all sampling plots,which were generally high in early morning and low in evening;obvious differences in PM2.5 and PM10 concentrations were observed among plant communities,which were most significant between the square plot and other plots;for the three functional areas,the blocking of PM2.5 and PM10 were all the strongest by the combined structure of arbor,shrub and grass,followed by arbor & shrub and arbor & grass structures,and the lowest by structure of shrub & grass and single structure of grass;the PM2.5 and PM10 concentrations were observed to be negatively correlated with temperature and wind speed,and positively correlated with relative humidity.

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张凌,郭悦,唐蒲霞,赵佳伦,王冬梦,刘艺平,孔德政.冬季不同植物群落对大气颗粒物浓度的阻滞作用[J].南京信息工程大学学报(自然科学版),2023,15(1):16-23
ZHANG Ling, GUO Yue, TANG Puxia, ZHAO Jialun, WANG Dongmeng, LIU Yiping, KONG Dezheng. Blocking effects of plant communities on atmospheric particles in winter[J]. Journal of Nanjing University of Information Science & Technology, 2023,15(1):16-23

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  • 收稿日期:2021-09-07
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  • 在线发布日期: 2023-02-17
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