首页|Fast increasing of surface ozone concentrations in Pearl River Delta characterized by a regional air quality monitoring network during 2006-2011

Fast increasing of surface ozone concentrations in Pearl River Delta characterized by a regional air quality monitoring network during 2006-2011

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Based on the observation by a Regional Air Quality Monitoring Network including 16 monitoring stations,temporal and spatial variations of ozone (O3),NO2 and total oxidant (Ox) were analyzed by both linear regression and cluster analysis.A fast increase of regional O3 concentrations of 0.86 ppbV/yr was found for the annual averaged values from 2006 to 2011 in Guangdong,China.Such fast O3 increase is accompanied by a correspondingly fast NOx reduction as indicated by a fast NO2 reduction rate of 0.61 ppbV/yr.Based on a cluster analysis,the monitoring stations were classified into two major categories-rural stations (non-urban) and suburban/urban stations.The O3 concentrations at rural stations were relatively conserved while those at suburban/urban stations showed a fast increase rate of 2.0 ppbV/yr accompanied by a NO2 reduction rate of 1.2 ppbV/yr.Moreover,a rapid increase of the averaged O3 concentrations in springtime (13％/yr referred to 2006 level) was observed,which may result from the increase of solar duration,reduction of precipitation in Guangdong and transport from Eastern Central China.Application of smog production algorithm showed that the photochemical O3 production is mainly volatile organic compounds (VOC)-controlled.However,the photochemical O3 production is sensitive to both NOx and VOC for O3 pollution episode.Accordingly,it is expected that a combined NOx and VOC reduction will be helpful for the reduction of the O3 pollution episodes in Pearl River Delta while stringent VOC emission control is in general required for the regional O3 pollution control.

O3cluster analysistemporal variationsmog production algorithmPearl River Delta

Jinfeng Li、Keding Lu、Wei Lv、Jun Li、Liuju Zhong、Yubo Ou、Duohong Chen

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College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China

Guangdong Provincial Environmental Monitoring Center, Guangzhou 510045, China

This work was supported by the National Natural Science Foundation of ChinaStrategic Priority Research Program of the Chinese Academy of SciencesNational Public Benefit Special Fund for Environmental Protection Researchand the Special Fund of State Key Joint Laboratory of Environment Simulation and Pollution Control

21190052,41121004XDB05010500201009001-413Z02ESPCP

2014

10.1016/S1001-0742(13)60377-0

环境科学学报(英文版)
中科院生态环境研究中心

环境科学学报(英文版)

CSTPCDCSCDSCIEI
影响因子：0.862
ISSN：1001-0742
年,卷(期)：2014.26(1)
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