Long-term measurements of surface ozone at remote and rural sites in China Xiaobin Xu 1, Weili Lin 1,2 1 Chinese Academy of Meteorological Sciences Key.

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Presentation transcript:

Long-term measurements of surface ozone at remote and rural sites in China Xiaobin Xu 1, Weili Lin 1,2 1 Chinese Academy of Meteorological Sciences Key Laboratory for Atmospheric Chemistry, CMA 2 Meteorological Observation Center, CMA TOAR Workshop 1.03, January 25-27, 2016

Outline Brief introduction Results from a baseline station Results from three background stations Summary

Chen et al. (1986) Ozone problem in Lanzhou  32 observation days during : 17 days with O 3 >100ppb ， 10 days with O 3 >200ppb; Photochemical pollution first found in Lanzhou during the later 1970s Causes: emissions from oil refining factory and power plant

More recent observations in Lanzhou: reduced O 3 levels, but still some high O 3 values Summer of 2006 J.M. Zhang, T. Wang*, A.J. Ding ， et al. (2009)

Higher O 3 levels were also observed in Beijing Ma & Zhang （ 2000 ） A clear increase trend in daily maximum

Some very high O 3 levels found in downwind of Beijing July 2005 maximum 286 ppb ！ Wang et al. (2006)

MOZAIC data indicated rapid increase of O 3 in PBL Ding et al. (2008)  PBL entire year ： 1 ppb/yr  PBL summer ： 3 ppb/yr

Operational observations surface O 3 at CMA’s GAW sites °N, °E, 310 m a.s.l ） 40.39°N, °E, m a.s.l °N ， °E ， 138 m a.s.l 36.3°N, 100.9°E, 3810m a.s.l °N,99.684°E ， 3582m asl °N ， °E, 750 m a.s.l 47.10°N, 87.93°E, 562m a.s.l In operation In construction WLG ： SDZ ： LA ： LFS ： XGLL ： AKDL ： Akedala Mt. Waliguan Shangdianzi Longfengshan Linan Jinsha Xianggelila

Previous one year measurements Ding et al （ 2001 ）  August 1994-July 1995  Higher background in western China  slightly polluted in eastern China LALFS WLG

More previous measurements from Linan, PEM-West A/B, China Map, etc. Xu et al. (2008)

Conclusion based on earlier O 3 data from LA ： O 3 variability was enhanced, probably caused by increase of the NO x level Xu et al. (2008)

Major results from the operational long-term measurements of surface O 3 at WLG, SDZ, LA, and LFS

Mt. Waliguan (WLG) WMO/GAW global baseline station  Very few population (about 6 persons km -2 )  Nearly no industry within 30 km

Hourly O 3 data from WLG The longest surface O 3 time series in mainland China

Average seasonal and diurnal variations Mountain-valley breeze effect:  Daytime minimum (more from PBL)  Nighttime maximum (more from the free troposphere)  Seasonal change of the timing of daily minimum Xu et al. (ACPD, 2015)

Linear and Mann-Kendall trends All Day Night MAM JJA SONDJFAll months Both methods give similar trends

 Increase trends in all seasons  Largest and significant increase in fall (2.8 ppb/10yr)  Smallest increase in winter (1.4 ppb/10yr)  Trends in summer much less significant Pollution from east of WLG seems not to be the main cause

Hilbert–Huang spectral analysis Some low frequency oscillations contributed significantly to the trends of O 3 at WLG. Changes of transport patterns, QBO, ENSO, STE, solar activity, etc.

Shangdianzi (SDZ) WMO/GAW regional background station

Long-term O 3 data from SDZ

SDZ Lin et al. (2008 ； 2009) North China Plain Significant contribution of pollutant transport from the North China Plain

Long-term trends Yearly mean Daily mean significant  =0.01 Slightly increasing

Yearly O 3 metrics for TOAR The three methods for getting 4 th highest 8-h average give the same results.

Yearly Mann-Kendall trends of O 3 metrics

Change of proportion of O 3 concentration in each bin Sen’s slope

AOT40, 3-month Increase trends of AOT40 in spring, summer and fall

Seasonal Mann-Kendall trends of O 3 metrics

O 3 exceedance GB Grade I: ~75 ppb Grade II: ~93 ppb ~10%

No significant trend in the ground- level NOx concentration

Tang et al. (2009) Zhang et al. (2007) Trend of surface NO x in urban area of BeijingTrend of tropospheric NO 2 over Beijing

Why increase of O 3 with decreasing NO x ？ Tang et al. (2009) Caused by increase of VOCs ？？

Ozone production efficiency (OPE) at SDZ Range ： 0.2~21.1; average ： 4.9±3.6 Ge et al. （ 2010 ）  Sensitive to VOCs and NOx, but mainly to VOCs The NOx level is too high in North China, O 3 is more sensitive to VOCs even at the background site.

Linan (LA) WMO/GAW regional background station located in the Yangtze Delta region, densely populated and industrialized 210 km 50 km Linan

O 3 data from LA

O 3 data analyzed in this work Strongly impacted by East Asia Monsoon

Long-term trends Slightly decreasing Not significant

No clear trend in high level O 3 metrics

Yearly Mann-Kendall trends of O 3 metrics Caution: only 9 years of data ( ) used

Change of proportion of O 3 concentration in each bin between 2006 and 2014 Slope from Linear regression None of these trends is statistically significant

AOT40, 3-month moving Spring and summer AOT40 values are not low, but there is no significant trend

Seasonal Mann-Kendall trends of O 3 metrics Minimum values are too close to the LOD

O 3 exceedance

Longfengshan (LFS) WMO/GAW regional background station ~140 km ~200 km ~130 km located in Northeast China, far away from major cities, but significantly impacted by agricultural activities (rice) Longfengshan

O 3 data from LFS

Long-term trends  Decrease trend  Lower significance

O 3 metrics

Change of proportion of O 3 concentration in each bin between 2006 and 2014 R 2 =0.42 R 2 =0.43 Slope from linear regression

O 3 exceedance

Average diurnal O 3 profiles from three regional background stations LFSLA SDZ Highest O 3 level Strongest photochemistry

Tropospheric NO 2 over east Asia Tropospheric NO 2 over east Asia Peters et al.(2005)

Gucheng: a rural site, 100 km southwest of Beijing Need to be analyzed

Summary Baseline O 3 in western China has been slightly increasing mainly due to dynamic processes. Regional background O 3 in North China has been rapidly increasing (0.73 ppb/yr). Many O 3 metrics show significant trends. Regional background O 3 in the Yangtze River Delta and Northeast China shows insignificant decreasing trends.

Thank you! Acknowledgement We thank all operators of the GAW stations for their routine work. The work is supported by Natural Science Foundation of China ( ) and Environmental Research in the Public Interest ( ).