SCIENCE CHINA Earth Sciences. Climatic change features of fog and haze in winter over North China and Huang-Huai Area

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1 SCIENCE CHINA Earth Sciences RESEARCH PAPER August 2015 Vol.58 No.8: doi: /s Climatic change features of fog and haze in winter over North China and Huang-Huai Area YIN ZhiCong 1,3, WANG HuiJun 1,2* & GUO WenLi 3 1 Nansen-Zhu International Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing , China; 2 Climate Change Research Center, Chinese Academy of Sciences, Beijing , China; 3 Beijing Meteorology Bureau, Beijing , China Received June 13, 2014; accepted December 16, 2014; published online May 7, 2015 This paper revealed the climatic change characteristics of fog and haze of different levels over North China and Huang-Huai area (NCHH). It was found that the haze-prone period has changed from winter into a whole year, and the haze days (HD) in winter have increased significantly. The foggy days (FD) are half of HD. There are little difference on the number of days and trends of fog at various levels. The HD and FD show no obvious positive correlation until the 1980s. Fog has larger spatial scale, showing more in the south than in the north. Haze occurs mainly around large cities with a discrete distribution. In the background of weakened East Asian Winter Monsoon (EAWM) and sufficient particulate matter, the negative correlation between haze and wind speed is weakened, but the positive correlation between haze and moisture conditions (precipitation and humidity) is significantly strengthened. In recent years, small wind and variability appear frequently. Meanwhile, as the stable source and strong moisture absorption of the aerosol particles, the moisture condition becomes one key control factor in the haze, especially wet haze with less visibility. In contrast, the FD presents a stable positive correlation with precipitation and relative humidity, but has no obvious negative correlation with wind speed. haze, fog, visibility, east asian winter monsoon, weather conditions Citation: Yin Z C, Wang H J, Guo W L Climatic change features of fog and haze in winter over North China and Huang-Huai Area. Science China: Earth Sciences, 58: , doi: /s *Corresponding author ( wanghj@mail.iap.ac.cn) In recent years, fog (referred to fog and mist definitions in the surface observation specification) and haze frequently and severely appeared all over China, which not only adversely affected the transportation, tourism, and other industries, but also caused health concerns throughout the country. Thus, governments at all levels have responded positively to develop air pollution control regulations or clean air plans. However, little systematic study and strict observation on haze have been done until Relatively more researches have been done on fog than on haze, but focused mainly on the diagnosis and simulation of one single foggy weather process. With the increasing severeness, fog and haze phenomena have gradually been classified into severe weather disasters. More concern and research have been focused on, and some important features have been revealed. Wu et al. (2010, 2011) pointed out the haze over urban areas in China significantly increased from 1951 to 2005, especially in North China, Huang-Huai, and Jiang-Huai regions. The foggy days (FD) in northern industrial cities showed an obvious interannual and decadal variation without a significant trend change. Gao (2008) and Song et al. (2013) also found the increasing trend of Haze days (HD) over many haze-prone regions in eastern China, for example, in western Henan. Sun et al. (2013) reached similar conclusions. The increased aerosols and climate Science China Press and Springer-Verlag Berlin Heidelberg 2015 earth.scichina.com link.springer.com

2 Yin Z C, et al. Sci China Earth Sci August (2015) Vol.58 No change may cause the reduced visibility and frequent occurrence of fog and haze (Che et al., 2007). Some scientists have specially discussed the change and cause of fog and haze over key areas. Che et al. (2009) studied the haze trends in 31 provincial capitals using the extinction coefficient as an indicator. Similar trends were found in Beijing, Shijiazhuang, Jinan, and Taiyuan. It seems that haze was strongly influenced by human activities. Zhao et al. (2011) conducted detailed diagnostic analysis on the visibility over Beijing, Tianjin, and Hebei (BTH). They found that the visibility over villages and towns was significantly higher than that in the cities. The visibility and PM 2.5 concentration were inversely correlated. Wang et al. (2013) pointed that the haze surge after the 1990s over BTH may be a comprehensive result of increased PM 2.5 concentration and weakened cold air activities. The decreasing Arctic sea ice is an important contributor to the recent increased haze days in eastern China and a significant signal for the short-term climate prediction (Wang et al., 2015). The climate change characteristics of fog and haze over NCHH were discussed in this paper. The observation data with four times a day were used for the first time to reconstruct the fog and haze climate sequence from 1961 to The spatial and temporal characteristics of fog and haze of various levels were compared and analyzed. In addition, the correlation between fog (haze) and climatic conditions were also discussed. The purpose of this paper was to find control factors besides the pollutant emissions, and to provide a scientific support for fog and haze governance and short-term climate prediction. 1 Data and methods There are mainly three types of fog and haze data processing methods at home and abroad: (1) Directly using the weather observation code (Gao, 2008; Song et al., 2013); (2) The climatic sequence is reconstructed by using the daily average data of visibility and relative humidity. The 90% relative humidity is defined to distinguish fog from haze (Wu et al, 2010, 2011); (3) Using the observation data at 14:00 to reconstruct climate sequence, and defining 90% relative humidity to distinguish fog from haze (Schich et al, 2001; Doyle and Dorling, 2002). There are obvious disadvantages after the comparative analysis: (1) The observation principle of haze was not unified until 2000, thus the weather observation code cannot be directly used in the climate research; (2) The relative humidity is difficult to achieve at 90%, thus haze is subjectively increased and fog is reduced; (3) Using the observation data of visibility and relative humidity at 14:00 is an internationally common method, which avoids early morning temperature inversion and light effect on the automatic visibility observation instrument. However, the visibility observation was manual before 2012, and fog & haze can happen at any time during one day in China. After quality control on the ground-timing observation data at 02, 08, 14, 20 from 1961 to 2012, 78 stations over NCHH were selected. The specific range is between N and E. It has been verified that the selected sites are evenly distributed (not shown) with reliable quality. Precipitation, blowing snow, blowing sand, dust storms and dust, and other weather phenomena affecting visibility are all excluded when reconstructing the climate sequence. Haze (fog) is defined when visibility less than 10 km and relative humidity smaller (larger) than 90%. A day with haze (fog) at any time is defined as a haze (foggy) day. In 1980, the national ground observation standard for visibility updated from grade to specific value (Li, 2010). The visibility data from 1961 to 1979 were classified into 0 9 levels with no specific values, which cannot be back calculated either. The visibility observation after 1980 presented specific value with an accuracy of 0.1 km. Therefore, the data after 1980 were converted into different levels when establishing the long-term climatic sequence. The level node features from 1961 to 1979 and standards of recent years were both taken into account in determining the division principles for four levels. The visibility was divided into four levels, correspondingly for fog and haze (Table 1). 2 Temporal change of fog and haze Figure 1 shows the days either with fog or haze (FD+HD_E), HD, FD and days with both fog & haze (FD+HD_B) from 1961 to Overall, the FD+HD_E presented a rapid upward trend before the 1980s, little change after the 1980s, and a slight decrease after It was found that 1973 was a mutation occurrence year after MK test (not shown). Similarly, the HD increased before the 1980s. The rising trend weakened after the 1980s and 1973 was a mutation year (MK-testing, not shown). The FD is half of HD, which increased before the 1980s and decreased after the 1980s. In other words, the FD+HD_E had no obvious change, but the FD decreased, the HD increased after the 1980s. In some way, the FD+HD_B explain the mutual conversion between fog and haze. The conversion was relatively frequent from 1981 to 2005, and then weakened after 2005 (Ding and Liu, 2014). Figure 1 shows that the monthly variation of HD is more and more obscure and that of FD is always obvious. It was Table 1 Levels of fog and haze in climatic sequence Level Visibility value (km) Level during Lv1 (slight) Lv2 (moderate) Lv3 (severe) Lv4 (extremely severe) <1 0 3

3 1372 Yin Z C, et al. Sci China Earth Sci August (2015) Vol.58 No.8 Figure 1 The variation of days either with fog or haze (a), haze days (b), fog days (c), and days of haze and fog both happened (d) from 1961 to 2012, monthly (curve), annual year (bar). Figure 2 Monthly variation of haze (red) and fog (black) days, (box), (smooth). found that the haze prone time has changed from winter into the whole year since 1993 by analyzing monthly variance and Figure 2. There is an average of haze days per month. The monthly and seasonal variations of FD show no obvious change. Summer is a fog prone season. August is the peak month with about 10 foggy days. There is an average of 5 foggy days per month in winter. 3 Spatial distributions of fog and haze in winter Figure 3 shows the significant difference between the spatial distributions of fog and haze in winter. Fog has a relatively larger spatial scale with more in the south than in the north. There are more than 20 foggy days south of Hebei and fewer than 10 foggy days north of Hebei. Haze is gathering mainly around large cities, such as Beijing, Tianjin, Hebei, Zhengzhou, Jinan, Taiyuan, and Xian with more than 40 haze days. But there are less haze surrounding small cit- ies and central Inner Mongolia. The single point correlation coefficient between 78 stations and provincial cities with relatively large interannual variability were calculated. In Figure 4, haze occurs around large cities and fog distribution is uniform, which reflects different formation mechanisms to some extent. In recent years, haze is composed mainly of fine particulate matter. The spatial distribution of haze has a close relationship with the pollution source. Fog is composed of a lot of droplets and the spatial distribution of which can be more easily affected by weather systems. The single-point correlation coefficient of haze shows two distinct positive and negative regions with different trends. There is an obvious negative correlation region over Inner Mongolia and Shanxi, and a significantly positive correlation region over other regions. Figures 5 and 6 show the latitude-time profile from 114 E to 118 E with more detailed characteristics on the north-south direction over BTH: (1) Three high-value haze centers appear over BTH, N, and south of 33 N. (2) Frequent haze first appeared over BTH. More than 25 slight haze days have emerged since 1961, more than 35 days since 1980, and over 45 days since The haze of Lv2 4 levels occurred mainly over BTH before 2000 and then declined slightly afterwards. (3) For the region between N, slight haze began to increase since 1970 and more than 55 days during the 1980s. Moderate haze has a similar trend, but obviously fewer days. Severe and extremely severe haze is always little. (4) Haze over south of 33 N area appeared later but increased rapidly, especially the moderate and severe haze since Compared with haze, fog variation is relatively simpler, showing features like more in the south than in the north, north-south synchronization, and significantly reduced in recent years. Fog also has a clearer interannual and decadal variability. It is noted that extremely severe fog has little north-south difference, even more in the north, the mechanism of which needs further study.

4 Yin Z C, et al. Figure 3 Figure 4 Sci China Earth Sci August (2015) Vol.58 No.8 Days of haze (a) and fog (b) in winter from 1961 to Single-point correlation coefficient of haze days ((a), Taiyuan) and fog days ((b), Shijiazhuang) in winter from 1961 to Figure 5 Latitude-time section of haze days in winter from 1961 to 2012, E mean. (a) Lv1; (b) Lv2; (c) Lv3; (d) Lv

5 1374 Yin Z C, et al. Sci China Earth Sci August (2015) Vol.58 No.8 Figure 6 Latitude-time section of foggy days in winter from 1961 to 2012, E mean. (a) Lv1; (b) Lv2; (c) Lv3; (d) Lv4. 4 Properties transition of fog and haze in winter The temporal changes were discussed in detail over the positive correlation region (31 42 N, E) in Figure 4. The haze of different levels exhibit different features (Figure 7(a)): (1) The HD-Lv1 increased markedly from 1961 to The HD-Lv1 remained stable at 35 days from 1981 to 2000, and slightly declined after 2000; (2) the trend of HD-Lv2 was similar with that of HD-Lv1 from 1961 to The HD-Lv2 down to six days or so from 1990 to 2000, and increased again after 2000 with enhanced annual variation as well; (3) severe haze had two processes of significant increase from 1980 to 2000 and occurred about 5 days after 2000; (4) the HD-Lv4 has been relatively stable at 1 day per winter. The differences between FD at varies levels are less significant. Obvious features are as follows: (1) The FD at different levels have significantly decreased during the past 10 years; (2) The interannual variability of FD is obvious; (3) The moderate and severe fogs have obvious decadal change, which presented continued negative anomaly from 1961 to 1980, positive anomaly from 1981 to 2000, and negative anomaly after No significant correlation existed between FD and HD before the 1980s, which indicates that fog and haze are two distinct weather phenomena (Figure 8). However, the correlation between fog and haze is significantly positive after the 1980s, which exceeds 95% confidence level. The correlation change is consistent well with FD+HD_B (Figure 1(d)). The boundaries between fog and haze have become blurred since the 1980s, which reflects more frequent conversion between fog and haze during one day. Energy consumption (or pollutant emission) plays a great role in promoting haze formation. However, HD does not monotonously increase with energy consumption. The interannual variability of HD is obvious after 1980 (Figure 9(a)). Figure 7 Haze (a) and fog (b) days in winter from 1961 to Haze of Lv1 refers to left vertical axis, the other 3 levels refer to right side. Figure 8 20-yr moving correlation between haze and fog days in winter from 1961 to 2012, horizontal line denoted 95% reliability.

6 Yin Z C, et al. Sci China Earth Sci August (2015) Vol.58 No absorption feature, which can hygroscopically grow quickly under adverse proliferation conditions with small wind. As a result, haze occurs and visibility reduces as well. Figure 11 (b) shows the reduced dependence of haze on the small wind speed. Generally, precipitation plays an indirect role in contributing to the haze occurrence. The weather situation is stable before rainfall (snowfall).there are small surface wind and increased humidity, which are the most favorable weather conditions for haze. After rainfall (snowfall), the maintenance of high humidity without significant cold air Figure 9 The variation of the haze-days (curve) and energy aggregate consumption in North China and Huang-Huai Area (bar, TCE) (a), and the haze-days (red) and EAWMI (black) (b). In addition, the correlation between EAWM index (Wang and He, 2012) and HD is 0.52, which exceeds 99% confidence level. The correlation indicates that weaker EAWM is more conductive to haze (Figure 9(b)), which is reflected by surface wind, relative humidity, rainfall, and other weather conditions. The surface wind in winter over NCHH showed a persistent decline, as well as the precipitation and relative humidity during the past 10 years (not shown). Figure 10(a) shows the 20-yr sliding correlation coefficient between HD and precipitation (relative humidity, wind speed) from 1961 to There are two distinct phases: (1) The correlation between HD and wind speed was significantly negative before the 1980s, which shows that smaller wind corresponds to more haze; (2) The HD was not so related with wind speed after the 1980s, but presented a significant positive correlation with precipitation and relative humidity, meaning that the greater precipitation (relative humidity), the more haze. Figure 11(a) shows the upward trend of relative humidity when haze happens, and slightly decline after The relative humidity was about 40% in the 1960s, and rose to 55% in 2000, which may be the result of the changing nature of haze. Before the reform and opening-up, haze was composed mainly of dust, dry dust, etc. Generally, dry environment is conducive to providing the dust sources for haze. Haze is likely to occur when under unfavorable diffusion conditions with small wind speed. With the booming economic development in China, lots of aerosol particles have been discharged into atmosphere, such as sulfate, nitrate, and organic hydrocarbons, etc. The aerosol particles have stable emission sources and strong moisture Figure yr moving correlation between haze/fog days and precipitation (relative humidity and wind)in winter from 1961 to 2012, horizontal dashed line denoted 95% reliability. (a) Haze days; (b) fog days. Figure 11 The relative humidity (a) and wind (b) when haze happened from 1961 to 2012.

7 1376 Yin Z C, et al. Sci China Earth Sci August (2015) Vol.58 No.8 will induce fog. Under current emission level, the pollutants can quickly return to a relatively high value after rainfall. The fog will convert to wet haze if without timely dispersion. The FD has a continuous positive correlation with precipitation (humidity) and a negative correlation with wind speed, which is sometimes less significant. The water evaporation after rainfall (snowfall) always makes the surface air close to saturation. Meanwhile, the ground longwave radiative cooling is obvious, which promotes the fog formation. Even without rainfall (snowfall), high relative humidity is a key factor for fog. In general, small wind speed is conducive for fog as well. 5 Discussion and conclusions The climatic change characteristics of fog and haze of different levels in winter over NCHH were revealed by analyzing the reconstructed data. The haze-prone period has changed from winter into the whole year. The HD in winter has increased significantly. The FD is half of HD and there are little differences on FD and trend at various levels. The HD and FD show no obvious correlation until the 1980s. Fog has larger spatial scale, showing more in the south than in the north. Haze occurs mainly around large cities with discrete distribution. The haze features are distinct over different gathering areas. The region over BTH began to have frequent haze since Haze over the area south of 33 N appeared relatively late, but grow rapidly with moderate and severe level after There are two dramatically different stages of haze in winter from 1961 to 2012: (1) the correlation between the HD and wind speed was significantly negative before the 1980s, and not so obvious after the 1980s; (2) the HD is significantly positive correlated with precipitation and relative humidity. In recent years, small wind and decreased wind speed variability frequently appear due to the weakened EAWM. Meanwhile, due to the stable source and strong moisture absorption of the aerosol particles, the moisture conditions become one key control factor to the haze, especially wet haze with less visibility. In contrast, the FD presents a stable positive correlation with precipitation and relative humidity, and no obvious negative correlation with wind speed. Fog and haze are not only two different phenomena with low visibility, but also present obvious difference in the change characteristics and formation mechanisms, which requires detailed study respectively. In particular, haze needs to be divided into two distinct phases when discussing the control factors. Some relations with haze are worth discussing, such as the weakened correlation between ENSO and EAWM (Wang et al., 2012), weakened EAWM itself (Wang et al., 2013; Zhang et al., 2014), low frequency oscillation, and the Arctic Oscillation. In addition to weather and climate conditions, the reasons affecting the distribution and trends of fog and haze include: (1) the development of urbanization leads to the reduction of surface wind speed, increased boundary layer thickness and temperature inversion changes, etc.; (2) pollutant sources emission and secondary pollution induced by industrial development; (3) policy adjustment, such as change from coal to gas, air pollution prevention, and the control policy like 2008 Beijing Olympic. All these reasons and weather conditions commonly regulate the spatial and temporal change of fog and haze. How these reasons interact with each other and to assess the specific gravity of each reason (Wang et al., 2014) are worth exploring. We thank the reviewers for their valuable advice and comments. This work was supported by the National Natural Science Foundation of China (Grant Nos , ). 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