Influence of Thermal Effects on Qinghai-Tibet Plateau on Air Quality

atmosphere

Article Inﬂuence of Thermal Eﬀects on Qinghai-Tibet Plateau on Air Quality in Typical Regions of China in Winter

Yanjun Li 1,3 , Xingqin An 2,3,*, Guangzhou Fan 1, Chao Wang 2,3, Yang Zhao 2 and Jiangtao Li 2,3

1 School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu 610225, China; [email protected] (Y.L.); [email protected] (G.F.) 2 State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China; [email protected] (C.W.); [email protected] (Y.Z.); [email protected] (J.L.) 3 Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China * Correspondence: [email protected]

Received: 6 November 2019; Accepted: 26 December 2019; Published: 30 December 2019

Abstract: In this paper, the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) monthly average reanalysis data from 1954 to 2017, haze days observation data from 1954 to 2017, and PM2.5 daily average mass concentration data from 2013 to 2017 are collected and collated. Firstly, the atmospheric apparent heat source on the Qinghai-Tibet Plateau is estimated based on thermodynamic equations. The correlation between the atmospheric apparent heat source (Q1) on the Qinghai-Tibet Plateau and the air quality in China, especially in the five typical regions (Beijing-Tianjin-Hebei, Fen-Wei Plain, Yangtze River Delta, Pearl River Delta, and Sichuan-Chongqing regions) is analyzed and studied. Through comprehensive diagnosis and synthesis, the differences of the three-dimensional spatial distribution of the circulation field and temperature field (planes and sections) in China and the typical regions in the strong and weak years of the apparent heat source Q1 on the Qinghai-Tibet Plateau in winter are compared, and the different distribution characteristics of the climate circulation background causing the strong and weak years of Q1 on the Qinghai-Tibet Plateau and the influence mechanism on the air quality in different regions in China are discussed. The results show that the spatial distribution of correlation between Q1 on the Qinghai-Tibet Plateau and PM2.5 in December has a northeast-southwest boundary. There is a negative correlation in the southeast region of the boundary, with heavy pollution when the cold source is strong and light pollution when the cold source is weak, while there is a positive correlation in the northwest region of the boundary, with light pollution when the cold source is strong and heavy pollution when the cold source is weak. The Q1 on Qinghai-Tibet Plateau is negatively correlated with air pollution in Beijing-Tianjin-Hebei and Fen-Wei Plain located in the northwest region of the boundary but positively correlated with air pollution in the Yangtze River Delta, Pearl River Delta, and Sichuan-Chongqing regions located in the southeast region of the boundary. In the cold source strong year, the northerly winds are stronger in the middle and high latitudes, and there is an abnormal northerly downward flow in the southeast region, thus the pollution is aggravated by the suppression of convection–diffusion in a downward flow. However, abnormal updraft in the northwest region exists, reducing pollution. In the cold source weak year, the situation is just the opposite.

Keywords: apparent heat source on Qinghai-Tibet plateau; air pollution; circulation background ﬁeld; boundary line; typical regions of China

Atmosphere 2020, 11, 50; doi:10.3390/atmos11010050 www.mdpi.com/journal/atmosphere Atmosphere 2020, 11, 50 2 of 17

1. Introduction Atmospheric heat source refers to non-adiabatic heating in the atmosphere, including heating the atmosphere in the form of sensible heat, condensation latent heat, and radiation heating, which is the driving force of atmospheric circulation. The Qinghai-Tibet Plateau accounts for a quarter of China’s land area, with an average altitude of more than 4000 m and about 1/3 of the troposphere height. It is the world’s largest plateau with the highest altitude and the most complex topography [1]. Ye et al. [2] and Flohn [3] pointed out that the Qinghai-Tibet Plateau was a powerful heat source in summer, transporting a large amount of heat and water vapor to the atmosphere in the central troposphere. Ye et al. [2] also pointed out for the first time that the Qinghai-Tibet Plateau was a cold source in winter. There are significant seasonal differences in the distribution of atmospheric heat sources/sinks over the Qinghai-Tibet Plateau. People have calculated and analyzed the atmospheric heating condition of the Qinghai-Tibet Plateau and found that the Qinghai-Tibet Plateau is a heat source for the whole year. There are two heat source-sink conversions each year, which are converted to a heat source in April and continue until September, with the strongest heat source months being June and July. The heat source turns into a cold source in October every year, with the strongest cold source in December [4–8]. In 1997, Wu et al. [9,10] put forward the “sensible heat pump” model. It was believed that the atmosphere over the Qinghai-Tibet Plateau sinks in winter and “discharges” to the periphery of the low altitude of the plateau. In summer, the atmosphere around the low altitude of the plateau is “pumped” up by the plateau and discharged outward in the upper troposphere. This cyclic pumping–discharging effect and the large-scale atmospheric rise-fall caused by it are like a giant “air pump” standing over the subtropical regions in the middle and east of Eurasia, which can effectively control the atmospheric circulation and seasonal climate changes in Asia and significantly affect the formation and changes of winter and summer monsoon in Asia. Yu et al. [11] summed up previous studies and believed that the heating effect of the Qinghai-Tibet Plateau had an important impact on the atmospheric circulation in the plateau and its surrounding areas. The possible mechanism is as follows: In the year when the heating intensity of the Qinghai-Tibet Plateau is strong, the upward movement, lower convergence and upper divergence of the plateau and its neighboring areas are all enhanced, which makes the suction effect of the plateau heating on the lower warm and humid air in the surrounding areas, and the discharge effect of the upper atmosphere to the surrounding areas are strengthened. At the same time, the summer water vapor transport in the eastern part of the southwest area is enhanced, and the water vapor convergence and upward movement are also enhanced, and vice versa. Studies have shown that the thermal effect of the Qinghai-Tibet Plateau has an important influence on the East Asian circulation and the local circulation in the downstream region [12–16], and also has an important influence on the atmospheric pollution in the downstream region. Previous researchers have analyzed the heat sources and sinks on the Qinghai-Tibet Plateau in different seasons in detail, and also have made detailed studies on the influence of heat source changes on atmospheric motion, but the influence on atmospheric pollution is relatively small. With the rapid growth of China’s national economy and the acceleration of industrialization and urbanization, the air pollution problem experienced by developed countries for more than 100 years has also occurred frequently in economically developed areas of China in the past 20 to 30 years. Xu et al. [17,18] have found that the heat source intensity on the Qinghai-Tibet Plateau in winter is significantly positively correlated with haze days in eastern China using data from 1980 to 2012. When the heat source on the Qinghai-Tibet Plateau is unusually warm in winter, the wind in East Asia is weak in winter, the northwest wind in eastern China is weakened, and the southwest wind is strengthened, thus enhancing the transportation of marine water vapor to eastern China, resulting in higher humidity in the lower atmosphere, which is conducive to the moisture absorption and growth of aerosols in eastern China. In addition, the lower atmosphere in eastern China has an obvious inversion structure and the pollution in eastern China is aggravated. According to the previous studies that the thermal effect of the Qinghai-Tibet Plateau has an obvious influence on the atmospheric circulation in the surrounding and downstream areas and the heat Atmosphere 2020, 11, 50 3 of 17 source/sink intensity of the Qinghai-Tibet Plateau has an obvious connection with the pollution situation in China in winter. However, is the influence of the atmospheric heat source of the Qinghai-Tibet Plateau on the pollution situation in different regions of China consistent in winter? If not, what are the possible influencing factors? The above problems are still unclear. Therefore, the relationship between the thermal effect of the Qinghai-Tibet Plateau in winter and the pollution of typical regions in China, and the related influencing mechanism are analyzed using longer-term data in this paper.

2. Information and Methods

2.1. Information Introduction The NCEP/NCAR global reanalysis data from 1954 to 2017 used in this paper included geopotential height, temperature, wind speed, and vertical velocity, etc., with 17 layers in the vertical direction and a 2.5 2.5 horizontal resolution. The PM mass concentration data used in this paper came × 2.5 from China’s air quality online monitoring platform, which carried out secondary veriﬁcation and statistics on the real-time data of 367 monitoring stations in the country provided by the Ministry of Environmental Protection, and ﬁnally released the daily air quality data of each city. The daily PM2.5 mass concentration data from 2013 to 2017 were selected, including 1498 stations in the country, and 902 stations with continuous observation data were selected for analysis in this paper. Haze day data came from the latest special haze day data set (V1.0) [19] compiled and updated by the national meteorological information center in 2018. The data set included the daily values of haze weather phenomena (including fog, light fog, and haze) observed by basic stations, benchmark weather stations, and general weather stations in China, and the regular visibility, relative humidity, and wind direction of 4 standard hours (00, 06, 12, and 18 UTC) each day. In the process of making this data set, 3 kinds of methods were applied: Climatic threshold value or allowable value check, internal consistency check, and spatial consistency check, to ensure that the data were under quality control, with good quality and complete data. Moreover, the “haze” phenomenon was observed in accordance with the requirements of “ground meteorological observation code” of China’s central meteorological administration. In this paper, 2444 sites with good data integrity in the whole country from 1958 to 2017 were selected for research.

2.2. Atmospheric Apparent Heat Source Q1 There are currently two main methods for calculating atmospheric heat sources. One is a positive algorithm or a direct algorithm, which uses direct observation data to calculate sensible heating, radiant heating, and condensation latent heat heating, respectively. Taking the 3 terms is the atmospheric heat source. The other is an inverse algorithm or indirect algorithm, which uses conventional meteorological data such as wind field, air temperature, and potential height to determine the apparent heat source of the atmosphere from the energy balance through the heat inflow equation. Both the calculation method and the data will lead to the uncertainty of the result. The positive algorithm can only obtain the entire layer of the heat source, while the inverted algorithm can obtain the vertical structure of the heat source, but the accuracy of the results depends on the accuracy of the reanalysis data [8,20]. In this study, the “inverse algorithm” was used to calculate the monthly heat source on the Qinghai-Tibet Plateau [21] over 75–100◦ E and 27.5–37.5◦ N. The apparent heat source Q1 formula is as follows: " # ∂T p k ∂θ Q1 = cp + V T + ( ) ω (1) ∂t ·∇ p0 ∂p where Q1 is the apparent heat source of each layer, T is the temperature, θ is the potential temperature, and ω is the vertical velocity of the p coordinate and assume that the vertical velocity at the top of the troposphere is 0. k = R/Cp, R and Cp are the dry air gas constant and specific heat at constant pressure, respectively. V is the horizontal wind vector, p0 is 1000 hPa. Q1 of each isostatic pressing layer can be calculated from Equation (1). Atmosphere 2019, 10, x FOR PEER REVIEW 4 of 17 Atmosphere 2020, 11, 50 4 of 17 constant pressure, respectively. V is the horizontal wind vector, 0 is 1000 hPa. Q1 of each isostatic pressing layer can be calculated from Equation (1). The vertical integral value of atmospheric apparent heat source can be expressed as: The vertical integral value of atmospheric apparent heat source can be expressed as: Z ps 11 (Q1) = Q1dp (2) (1) =g 1 (2) pt where (Q1)) is is the entire apparent heat source, ps and ptt areare the the ground ground pressure and atmospheric top pressure (taking 100 hPa), respectively,respectively, andand gg isis thethe gravitationalgravitational acceleration.acceleration. The integralintegral valuevalueQ Q1 of1 of the the whole whole layer layer of the of apparentthe apparent heat sourceheat source over the over Qinghai-Tibet the Qinghai-Tibet Plateau Plateaurepresents represents the thermal the thermal effect of effect the Qinghai-Tibet of the Qingha Plateau.i-Tibet Plateau. December December with the with strongest the strongest cold source cold sourcerepresenting representing winter is winter selected is forselected research for in research this paper. in this The paper. standardized The standardized apparent heat apparent source Q heat1 on sourcethe Qinghai-Tibet Q1 on the Qinghai-Tibet plateau from December plateau from 1954 December to 2017, which 1954 was to 2017, used thewhichZ-score was method,used the is Z shown-score method,in Figure is1. shown in Figure 1.

Figure 1. StandardizedStandardized apparent apparent heat heat source source QQ1 of1 of Qinghai-Tibet Qinghai-Tibet Plateau Plateau in inDecember December from from 1954 1954 to 2017.to 2017.

2.3. Selection Selection of Strong and Weak Years of Apparent HeatHeat SourceSource QQ11 on the Qinghai-Tibet PlateauPlateau inin WinterWinter In orderorder toto find find more more obvious obvious characteristics characteristics of strong of strong and weakand weak cold source cold source years, onyears, the premise on the of having enough samples, we tried to select the target years with 1.2 as the standard according to the premise of having enough samples, we tried to select the target± years with ±1.2 as the standard accordingstandardized to Qinghai-Tibetthe standardized plateau Qinghai-Tibet heat source plateauQ1 from heat 1954 source to 2017, Q1 and from the 1954 standard to 2017, was and slightly the stricter than 1. The years with an index less than 1.2 were determined as cold source strong years. standard was± slightly stricter than ±1. The years with− an index less than −1.2 were determined as cold Thesource years strong which years. met The the standardyears which were met 1959, the 1960, standa 1965,rd were 1996, 1959, 1997, 2007,1960, 2011,1965, 2013,1996, and1997, 2014, 2007, and 2011, the years2013, and with 2014, an index and the greater years than with 1.2 an were index cold greater source than weak 1.2 were years, cold including source 1956,weak 1967,years, 1968, including 1974, 1986,1956, 1967, 1989, 1968, 2005, 1974, and 2010. 1986, The1989, correlation 2005, and analysis2010. The and correlation synthesis analysis analysis and were synthesis used in analysis this paper. were used in this paper. 3. Results 3. Results 3.1. Relationship between the Apparent Heat Source Q1 on the Qinghai-Tibet Plateau and Air Pollution in China 3.1. Relationship between the Apparent Heat Source Q1 on the Qinghai-Tibet Plateau and Air Pollution in China3.1.1. Spatial Distribution Characteristics of Correlation between the Apparent Heat Source Q1 on the Qinghai-Tibet Plateau and PM2.5 Concentration in China 3.1.1. Spatial Distribution Characteristics of Correlation between the Apparent Heat Source Q1 on The mass concentration of PM2.5 in December at the national stations from 2013 to 2017 and the Qinghai-Tibet Plateau and PM2.5 Concentration in China the apparent heat source Q1 on the Qinghai-Tibet Plateau during the same period were analyzed for correlations.The mass concentration The stations of with PM correlation2.5 in December coeffi atcients the national higher thanstations 0.7 from (reddots) 2013 andto 2017 lower and than the apparent0.7 (blue heat dots) source are shown Q1 on in the Figure Qinghai-Tibet2. All stations Plateau in the during figure havethe same passed period the 80% were confidence analyzed test. for − Ascorrelations. can be seen The from stations Figure with2, the co correlationrrelation coefficients between the higher apparent than heat 0.7 source(red dots)Q1 onand the lower Qinghai-Tibet than −0.7 plateau(blue dots) and are PM shown2.5 concentration in Figure 2. hadAll stations an obvious in the northeast-southwest figure have passed boundary. the 80% confidence In the northwest test. As canregion be ofseen the from boundary, Figure the 2, the PM correla2.5 concentrationtion between and the the apparent apparent heat heat source source QQ11 onon the the Qinghai-Tibet Qinghai-Tibet plateau and PM2.5 concentration had an obvious northeast-southwest boundary. In the northwest

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region of the boundary, the PM2.5 concentration and the apparent heat source Q1 on the Qinghai-Tibet plateau were mainly positively correlated, while in the southeast region of the boundary, they were negatively positively correlated.

Figure 2. Spatial distribution characteristics of the correlation between the apparent heat source Q1 Figure 2. Spatial distribution characteristics of the correlation between the apparent heat source Q1 on on the Qinghai-Tibet plateau and PM2.5 concentration in China and five typical regions. The boxes inthe the Qinghai-Tibet figure are, respectively, plateau and fivePM2.5 typical concentration polluted in areas: China 1. and Beijing-Tianjin-Hebei, five typical regions. 2. The Fenwei boxes Plain, in the 3. Chengdu-Chongqing,figure are, respectively, 4. Pearlfive Rivertypical Delta, polluted and 5.area Yangtzes: 1. Beijing-Tianjin-Hebe River Delta. i, 2. Fenwei Plain, 3. Chengdu-Chongqing, 4. Pearl River Delta, and 5. Yangtze River Delta.

Among the five typical pollution areas, the apparent heat source Q1 on the Qinghai-Tibet plateau Among the five typical pollution areas, the apparent heat source Q1 on the Qinghai-Tibet plateau and the concentration of PM2.5 were mainly positively correlated in the Beijing-Tianjin-Hebei region and Fen-Weithe concentration plain. That of wasPM2.5 the were stronger mainly the positively cold source correlated of the Qinghai-Tibet in the Beijing-Tianjin-Hebei plateau, the lower region the and Fen-Wei plain. That was the stronger the cold source of the Qinghai-Tibet plateau, the lower the mass concentration of PM2.5 in the Beijing-Tianjin-Hebei region and the Fen-Wei plain, the weaker mass concentration of PM2.5 in the Beijing-Tianjin-Hebei region and the Fen-Wei plain, the weaker the cold source of the Qinghai-Tibet plateau and the higher the concentration of PM2.5 in these two the cold source of the Qinghai-Tibet plateau and the higher the concentration of PM2.5 in these two regions. However, the apparent heat source Q1 on the Qinghai-Tibet plateau and the concentration of regions. However, the apparent heat source Q1 on the Qinghai-Tibet plateau and the concentration PM2.5 were obviously negatively correlated in the Yangtze River Delta, Sichuan-Chongqing, and the Pearlof PM River2.5 were Delta obviously regions. negatively That was, correlated the stronger in the the Yangtze cold source River on Delta, the Qinghai-Tibet Sichuan-Chongqing, Plateau, and the heavierthe Pearl the River pollution Delta inregions. these three That regions;was, the the strong weakerer the the cold cold source source on on the the Qinghai-Tibet Qinghai-Tibet Plateau, andthe heavier the lighter the the pollution pollution. in these three regions; the weaker the cold source on the Qinghai-Tibet Plateau, and the lighter the pollution. 3.1.2. Correlation between the Apparent Heat Source Q1 on the Qinghai-Tibet Plateau and PM2.5 Concentration3.1.2. Correlation in Fivebetween Typical the RegionsApparent Heat Source Q1 on the Qinghai-Tibet Plateau and PM2.5 Concentration in Five Typical Regions The time series of the average PM2.5 mass concentration of five typical regional observation stationsThe in time December series fromof the 2013 average to 2017 PM and2.5 mass the apparent concentration heat source of fiveQ1 typicalon the Qinghai-Tibetregional observation Plateau duringstations the in sameDecember period from are 2013 shown to inDecember Figure3. 2017 The averageand the PMapparent2.5 mass heat concentrations source Q1 on of the five Qinghai- typical regionalTibet Plateau observation during the stations same fromperiod 2013 are toshown 2017 in in Figure December 3. The and average the apparent PM2.5 mass heat concentrations source Q1 of theof five Qinghai-Tibet typical regional Plateau observation during the stations same period from were2013 to taken 2017 as in a timeDecember series, and and the their apparent correlations heat weresource analyzed. Q1 of the Qinghai-Tibet As shown inFigure Plateau3, during the Beijing-Tianjin-Hebei the same period were region taken (Figure as a time3a), series, Fen-Wei and plain their (Figurecorrelations3b), Yangtze were analyzed. River Delta As shown (Figure in3c), Figure Sichuan-Chongqing 3, the Beijing-Tianjin-Hebei region (Figure region3d), and (Figure Pearl 3a), River Fen- DeltaWei plain (Figure (Figure3e) were, 3b), respectively,Yangtze River from Delta top (Figure to bottom. 3c), ForSichuan-Chongqing each region, we used region 84, (Figure 59, 163, 3d), 44, andand 87Pearl data River points Delta in calculating(Figure 3e) thewere, averages respectively, of PM2.5 from. top to bottom. For each region, we used 84, 59, 163, 44, and 87 data points in calculating the averages of PM2.5.

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Figure 3. Correlation between the apparent heat source Q1 on the Qinghai-Tibet plateau and PM2.5 Figureconcentration 3. Correlation in typical between areas ofthe China. apparent heat source Q1 on the Qinghai-Tibet plateau and PM2.5 concentration in typical areas of China. As can be seen from Figure3, the mass concentration of PM 2.5 in the Beijing-Tianjin-Hebei region and Fen-Wei Plain was positively correlated with the time series of apparent heat source Q1 of the As can be seen from Figure 3, the mass concentration of PM2.5 in the Beijing-Tianjin-Hebei region Qinghai-Tibet Plateau, with correlation coefficients of 0.20 and 0.46, respectively. In 2014, the cold and Fen-Wei Plain was positively correlated with the time series of apparent heat source Q1 of the source on the Qinghai-Tibet Plateau was relatively strong, and the mass concentration of PM2.5 Qinghai-Tibetdecreased inPlateau, the two with regions. correlation And in 2015–2016, coefficients the of cold 0.20 source and on0.46, the respectively. Qinghai-Tibet In Plateau 2014, wasthe cold source on the Qinghai-Tibet Plateau was relatively strong, and the mass concentration of PM2.5 relatively weak and the mass concentration of PM2.5 was relatively high. However, in 2017, the cold decreasedsource ofin Qinghai-Tibetthe two regions. Plateau And increased in 2015–2016, while the th masse cold concentration source on the of PMQinghai-Tibet2.5 decreased Plateau in these was relativelytwo regions. weak and the mass concentration of PM2.5 was relatively high. However, in 2017, the cold source ofWhile Qinghai-Tibet the PM2.5 concentrationPlateau increa insed the while other the three mass typical concentration regions of theof PM Yangtze2.5 decreased River Delta, in these two Sichuan-Chongqingregions. region, and Pearl River Delta was negatively correlated with Q1, with correlation coefficients of 0.63, 0.57, and 0.73, respectively. In 2013, the cold source on the Qinghai-Tibet While the PM− 2.5 concentration− − in the other three typical regions of the Yangtze River Delta, Plateau was strong and the concentration of PM was high. From 2014 to 2016, the cold source on the Sichuan-Chongqing region, and Pearl River Delta2.5 was negatively correlated with Q1, with correlation Qinghai-Tibet Plateau weakened and the mass concentration of PM in the three regions decreased. coefficients of −0.63, −0.57, and −0.73, respectively. In 2013, the 2.5cold source on the Qinghai-Tibet And from 2016 to 2017, the cold source on the Qinghai-Tibet Plateau became stronger while the mass Plateau was strong and the concentration of PM2.5 was high. From 2014 to 2016, the cold source on concentration of PM2.5 in the three regions increased. the Qinghai-TibetFrom 2014 toPlateau 2016, theweakened cold source and on the the mass Qinghai-Tibet concentration Plateau of weakened PM2.5 inwhile the three the mass regions decreased. And from 2016 to 2017, the cold source on the Qinghai-Tibet Plateau became stronger concentration of PM2.5 in the Yangtze River Delta and Pearl River Delta decreased. From 2016 to 2017, whilethe the cold mass source concentration on the Qinghai-Tibet of PM2.5 Plateauin the three increased regions while increased. the mass concentration of PM2.5 in the YangtzeFrom 2014 River to Delta 2016, and the Pearl cold River source Delta on increased. the Qinghai-Tibet Plateau weakened while the mass concentration of PM2.5 in the Yangtze River Delta and Pearl River Delta decreased. From 2016 to 2017, 3.1.3. Correlation between the Apparent Heat Source Q1 on the Qinghai-Tibet Plateau and the cold source on the Qinghai-Tibet Plateau increased while the mass concentration of PM2.5 in the Concentration of PM2.5 in Typical Cities Yangtze River Delta and Pearl River Delta increased. In the five typical regions, the representative cities were selected for the time series of PM2.5 mass concentration and the apparent heat source Q on the Qinghai-Tibet plateau from December 3.1.3. Correlation between the Apparent Heat Source1 Q1 on the Qinghai-Tibet Plateau and 2013 to December 2017. As shown in Figure4, the representative cities were Beijing (Figure4a), Concentration of PM2.5 in Typical Cities Baoji (Figure4b), Shanghai (Figure4c), Chongqing (Figure4d), and Shenzhen (Figure4e), and their correlationIn the five was typical consistent regions, with the the representative typical regions. cities were selected for the time series of PM2.5 mass concentration and the apparent heat source Q1 on the Qinghai-Tibet plateau from December 2013 to December 2017. As shown in Figure 4, the representative cities were Beijing (Figure 4a), Baoji (Figure 4b), Shanghai (Figure 4c), Chongqing (Figure 4d), and Shenzhen (Figure 4e), and their correlation was consistent with the typical regions.

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Figure 4. Correlation between the apparent heat source Q1 of the Qinghai-Tibet plateau and PM2.5 Figureconcentration 4. Correlation of the between representative the apparent cities of typical heat regionssource inQ China;1 of the (* meansQinghai-Tibet passing the plateau single-tailed and PM2.5 concentration95% confidence of the test, representative ** means passing cities the of single-tailedtypical regions 99% in confidence China; (* test). means passing the single-tailed 95% confidence test, ** means passing the single-tailed 99% confidence test). The mass concentration of PM2.5 in Beijing and Baoji was significantly positively correlated with the apparent heat source Q1 on the Qinghai-Tibet Plateau, with correlation coefficients of 0.65 The mass concentration of PM2.5 in Beijing and Baoji was significantly positively correlated with and 0.90, respectively. The correlation coefficient of Baoji passed the 95% confidence test. The mass the apparent heat source Q1 on the Qinghai-Tibet Plateau, with correlation coefficients of 0.65 and concentration of PM2.5 in Shanghai, Chongqing, and Shenzhen had a significant negative correlation 0.90,with respectively. the apparent The heat correlation source Q on coefficient the Qinghai-Tibet of Baoji Plateau, passed with the correlation 95% confidence coefficients test. of The0.70, mass 1 − concentration0.99, and of0.88, PM2.5 respectively, in Shanghai, of whichChongqing, Chongqing and Shenzhen passed the had 95% a confidence significant test negative and Shenzhen correlation − − withpassed the apparent the 99% heat confidence source test. Q1 on the Qinghai-Tibet Plateau, with correlation coefficients of −0.70, −0.99, and −0.88, respectively, of which Chongqing passed the 95% confidence test and Shenzhen passed3.2. the Analysis 99% ofconfidence Circulation test. and Temperature Fields in Strong and Weak Years of the Apparent Heat Source Q1 on the Qinghai-Tibet Plateau

3.2. Analysis3.2.1. General of Circulation Circulation and Situation Temperature Fields in Strong and Weak Years of the Apparent Heat Source Q1 on the Qinghai-Tibet Plateau In the cold source weak year, the sea level field in most areas of our country, there was abnormal cold high pressure, but there was a weak thermal low pressure only in the Guangxi and Yunnan province, 3.2.1. General Circulation Situation causing a weak convergence rise (Figure5b). 500 hPa south branch groove deepens guiding the 850 hPa southerlyIn the cold airflow source northward, weak year, which the sea changed level field intoa in westerly most areas airflow of our due country, to the topography there was ofabnormal the coldQinghai-Tibet high pressure, plateau but andthere then was into a anweak abnormal thermal southwesterly low pressure airflow only in southwestin the Guangxi China. However,and Yunnan province,there wascausing also ana weak abnormal convergence low potential rise at (Figure 500 hPa 5b). from 500 the hPa western south Pacific branch to groove Beijing-Tianjin-Hebei deepens guiding region. The easterly airflow at 850 hPa in the northeast region was strengthened and changed to the the 850 hPa southerly airflow northward, which changed into a westerly airflow due to the northerly airflow in the Beijing-Tianjin-Hebei region, which merged with the southwest airflow from topography of the Qinghai-Tibet plateau and then into an abnormal southwesterly airflow in the southwest region at about 35◦ N region (Figure5d). southwestAt China. 200 hPa, However, the westerly there anomaly was also in the an year abnormal with strong low cold potential source at appeared 500 hPa from from the the central western PacificQinghai-Tibet to Beijing-Tianjin-Hebei Plateau to Qinghai, region. while The it appeared easterly in Indiaairflow and at Bay 850 of hPa Bengal in inthe the northeast year with region a weak was strengthenedcold source. and Therefore, changed the to westerly the northerly anomaly airflow in the yearin the with Beijing-Tianjin-Hebei a strong cold source wasregion, more which northerly merged withand the easterlysouthwest than airflow that in the from year the with southwest a weak cold region source at (Figureabout 35°5e,f). N region (Figure 5d). At 200 hPa, the westerly anomaly in the year with strong cold source appeared from the central Qinghai-Tibet Plateau to Qinghai, while it appeared in India and Bay of Bengal in the year with a weak cold source. Therefore, the westerly anomaly in the year with a strong cold source was more northerly and easterly than that in the year with a weak cold source (Figure 5e,f).

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(a) (b)

(e) (f)

Figure 5. Sea level temperature and air pressure (a,b), units (C˚ and Pa), 850 hPa uv wind and 500 hPa Figure 5. Sea level temperature and air pressure (a,b), units (◦C and Pa), 850 hPa uv wind and 500 hPa Commented [M14]: We have moved it here, please confirm potential height (c,d), units (m/s and m), 200 hPa latitudinal wind speed (e,f), units (m/s) in Q1 strong potential height (c,d), units (m/s and m), 200 hPa latitudinal wind speed (e,f), units (m/s) in Q1 strong it and weak year and their differences (strong–weak year). a, c, e for a strong year, b, d, f for a weak and weak year and their differences (strong–weak year). (a,c,e) for a strong year, (b,d,f) for a weak year. year. Commented [liyj15R14]: Yes, we confirm it. 3.2.2. Profile of the Wind Field and Temperature Field in Five Typical Pollution Areas 3.2.2. Profile of the Wind Field and Temperature Field in Five Typical Pollution Areas (1) Beijing-Tianjin-Hebei Region (1) Beijing-Tianjin-Hebei Region In the Beijing-Tianjin-Hebei region, PM2.5 concentration was positively correlated with the In the Beijing-Tianjin-Hebei region, PM2.5 concentration was positively correlated with the apparent heat source Q on the Qinghai-Tibet plateau. That was, the stronger the cold source on the apparent heat source1 Q1 on the Qinghai-Tibet plateau. That was, the stronger the cold source on the Qinghai-TibetQinghai-Tibet plateau plateau in in winter, winter, the the pollution pollution inin the Beijing Beijing-Tianjin-Hebei-Tianjin-Hebei region region decrease decreased,d, while while the pollutionthe pollution increased increase whend when the the cold cold source source weakened.weakened. In In order order to toinvestigate investigate the thereason reason for the for the existence of this correlation characteristic from the circulation field, the wind field, and temperature field were, respectively, made along 40◦ N and 105◦ E. The analysis showed that in the year of the strong cold source (upper left Figure6), the lower layer was the abnormal west-west downward flow Atmosphere 2019, 10, x FOR PEER REVIEW 9 of 17

and weak year and their differences (strong–weak year). (a,c,e) for a strong year, (b,d,f) for a weak year.

3.2.2. Profile of the Wind Field and Temperature Field in Five Typical Pollution Areas (1) Beijing-Tianjin-Hebei Region In the Beijing-Tianjin-Hebei region, PM2.5 concentration was positively correlated with the apparent heat source Q1 on the Qinghai-Tibet plateau. That was, the stronger the cold source on the Qinghai-Tibet plateau in winter, the pollution in the Beijing-Tianjin-Hebei region decreased, while the pollution increased when the cold source weakened. In order to investigate the reason for the existence of this correlation characteristic from the circulation field, the wind field, and temperature Atmosphere 2020, 11, 50 9 of 17 field were, respectively, made along 40° N and 105° E. The analysis showed that in the year of the strong cold source (upper left Figure 6), the lower layer was the abnormal west-west downward flow onon the the east-west east-west section section of of the the Beijing-Tianjin-Hebei Beijing-Tianjin-Hebei region, region, and, and, the the abnormally abnormally high high temperature temperature weakenedweakened thethe sinking component component of of the the wind. wind. In Inthe the year year of the of weak the weak cold coldsource source (upper (upper right Figure right Figure6), the6 ),east-west the east-west section section had abnormal had abnormal airflow airflow rising rising to the to east, the while east, while the abnormal the abnormal “inversion “inversion layer” layer”existed, existed, which which inhibited inhibited the rising the rising airflow. airflow. In addi Intion, addition, the reduction the reduction of horizontal of horizontal wind wind speed speed near nearthe ground the ground was wasaffected affected by the by terrain, the terrain, whic whichh was was conducive conducive to pollutant to pollutant accumulation. accumulation. TheThe verticalvertical section of of the the north-south north-south wind wind field field and andtemperature temperature field fieldalong along105° E 105 in Beijing-◦ E in Beijing-Tianjin-HebeiTianjin-Hebei (36°–40° (36–40 N) showed◦ N) showed that in the that cold in the source cold strong source year strong (lower year left (lower Figure left 6), Figure there 6was), therean abnormal was an abnormal northerly northerly downward downward flow from flow north from to south, north toand south, the higher and the temperature higher temperature in the lower in thelayer lower weakened layer weakened the sinking the component, sinking component, which was which conducive was conduciveto transporting to transporting pollutants southward. pollutants southward.However, in However, the year of in the the weak year ofcold the source weak cold(lower source right (lowerFigure right6), the Figure inversion6), the layer inversion inhibited layer the inhibitedlocal updraft, the local and updraft, there was and a thereweak was southerly a weak airflow, southerly which airflow, transported which transported pollutants pollutants from the fromsouth thearea south of Beijing-Tianjin-Hebei area of Beijing-Tianjin-Hebei to the north, to the whic north,h was which blocked was blockedby the Yans by thehan Yanshan Mountain Mountain and reduced and reducedthe horizontal the horizontal wind speed, wind resulting speed, resulting in pollutant in pollutant accumulation. accumulation.

FigureFigure 6. 6.Circulation Circulation andand temperaturetemperature ﬁeldsfields inin the the east-west east-west section section ( top(top)) and and north-south north-south section section (bottom(bottom)) of of Beijing-Tianjin-Hebei Beijing-Tianjin-Hebei region region in in strong strong ( left(left)) and and weak weak ( right(right)) cold cold source source years years on on the the Qinghai-TibetQinghai-Tibet plateau. plateau.

(2) Fen-Wei Plain The situation in the Fen-Wei Plain was similar to that in Beijing-Tianjin-Hebei Region, and PM2.5 concentration was positively correlated with the apparent heat source Q1 on the Qinghai-Tibet Plateau. In the cold source strong year of the Qinghai-Tibet Plateau, there was an abnormal easterly wind near the ground on the east-west vertical section (upper left Figure 7) along 35° N in Fen-Wei Plain (107°–112° E), and the abnormal warm near-surface temperature was conducive to the upward- lifting of pollutants, which was guided away from the plain by the abnormal easterly rising airflow at 700 hPa, while the easterly airflow in the eastern region (about 115° E) was affected by the sinking componentAtmosphere 2020 and, 11 ,sunk 50 along the terrain, which was not conducive to the transportation of pollutants10 of 17 to the Fen-Wei Plain and the reduction of pollution conditions. However, in the cold source weak yearFigure (upper7), the right temperature Figure 7), belowthe temperature 500 hPa in below the Fen-Wei 500 hPa Plain in the was Fen-Wei abnormally Plain was cold, abnormally which inhibited cold, which inhibited vertical diffusion. Moreover, the abnormal downward flow of 105° E and the easterly vertical diffusion. Moreover, the abnormal downward flow of 105◦ E and the easterly updraft from updraft from Henan and other places near 115° E moved along the terrain and merged in the near- Henan and other places near 115◦ E moved along the terrain and merged in the near-surface of Fen-Wei surfacePlain, resultingof Fen-Wei in increasedPlain, resulting pollution in increased in the plain. pollution in the plain. On the vertical section along 110° E in the north-south direction of Fen-Wei Plain (from 34° to On the vertical section along 110◦ E in the north-south direction of Fen-Wei Plain (from 34◦ 36° N), there was an abnormal northerly wind in the year of the strong cold source (lower left Figure to 36◦ N), there was an abnormal northerly wind in the year of the strong cold source (lower left 7)Figure and 7abnormal) and abnormal warm warm temperature temperature in the in thelower lower layer, layer, which which was was favorable favorable for for transporting pollutantspollutants southward southward along along the the terrain. terrain. In In the the cold cold so sourceurce weak weak year year (lower (lower right right Figure Figure 7),7), there there was was aa southerly southerly airflow airflow rising rising along along the the terrain, terrain, and and the the temperature temperature in in the the lower lower layer layer was was abnormally abnormally cold,cold, which which was was conducive conducive to to inhibiting inhibiting the the rising rising airflow, airflow, resulting resulting in in the the accumulation accumulation of of pollutants pollutants inin the the Fen-Wei Fen-Wei Plain. Plain.

Figure 7. Circulation and temperature ﬁelds in the east-west (top) and north-south (bottom) cross-sections of the Fen-Wei Plain region in strong (left) and weak (right) cold source years of Figure 7. Circulation and temperature fields in the east-west (top) and north-south (bottom) cross- the Qinghai-Tibet plateau. sections of the Fen-Wei Plain region in strong (left) and weak (right) cold source years of the Qinghai- Tibet(3) Yangtze plateau. River Delta In the Yangtze River Delta region, PM2.5 concentration was negatively correlated with the apparent (3) Yangtze River Delta heat source Q1 on the Qinghai-Tibet Plateau. In the cold source year, there was an abnormally strong

“inversion cover” on the east-west vertical section of the Yangtze River Delta region (118–122◦ E) along 30◦ N (upper left Figure8), which was conducive to inhibiting vertical movement. Moreover, the west downward flow sinking along the Qinghai-Tibet Plateau below 850 hPa entrained pollutants passing through the region into the Yangtze River Delta region, which aggravated pollution. However, in weak years (upper right Figure8), the westerly airflow sinking along the mountains rose at about 105◦ N, and the subsidence through the Yangtze River Delta region was unusually weak. Moreover, the westerly airflow near 117.5◦ E turned into uplifting airflow, which was conducive to the vertical diffusion of pollutants. Atmosphere 2019, 10, x FOR PEER REVIEW 11 of 17

In the Yangtze River Delta region, PM2.5 concentration was negatively correlated with the apparent heat source Q1 on the Qinghai-Tibet Plateau. In the cold source year, there was an abnormally strong “inversion cover” on the east-west vertical section of the Yangtze River Delta region (118°–122° E) along 30° N (upper left Figure 8), which was conducive to inhibiting vertical movement. Moreover, the west downward flow sinking along the Qinghai-Tibet Plateau below 850 hPa entrained pollutants passing through the region into the Yangtze River Delta region, which aggravated pollution. However, in weak years (upper right Figure 8), the westerly airflow sinking along the mountains rose at about 105° N, and the subsidence through the Yangtze River Delta region Atmosphere 2020, 11, 50 11 of 17 was unusually weak. Moreover, the westerly airflow near 117.5° E turned into uplifting airflow, which was conducive to the vertical diffusion of pollutants.

On the vertical section of the Yangtze River Delta (27°–34° (27–34◦ N) N) inin thethe south-northsouth-north directiondirection alongalong 120120°◦ E, inin thethe strongstrong coldcold sourcesource yearyear (lower(lower left FigureFigure8 8),), thethe downwarddownward flowflow onon thethe northnorth sideside ofof about 800800 hPahPa overover the the Yangtze Yangtze River River Delta Delta inhibited inhibited weak weak uplift uplift airflow airflow at the at lowerthe lower level, level, which which was notwas conducive not conducive to the to vertical the vertical diffusion diffusion of pollutants. of pollutants. However, However, in the coldin the source cold source weak year weak (lower year right(lower Figure right8 Figure), there 8), was there a consistent was a consistent uplift airflowuplift airflow over the over Yangtze the Yangtze River River Delta Delta region, region, which which was conducivewas conducive to the to vertical the vertical diffusion diffusion of pollutants. of pollutants.

Figure 8. Circulation and temperature fields in the east-west (top) and north-south (bottom) Figure 8. Circulation and temperature fields in the east-west (top) and north-south (bottom) cross- cross-sections of the Yangtze River Delta region in strong (left) and weak (right) cold source years on sections of the Yangtze River Delta region in strong (left) and weak (right) cold source years on the the Qinghai-Tibet plateau. Qinghai-Tibet plateau. (4) Sichuan-Chongqing Region (4) Sichuan-Chongqing Region In the Sichuan-Chongqing regions, PM2.5 concentration was negatively correlated with the In the Sichuan-Chongqing regions, PM2.5 concentration was negatively correlated with the apparent heat source Q1 on the Qinghai-Tibet Plateau. In the year of strong cold source on the apparent heat source Q1 on the Qinghai-Tibet Plateau. In the year of strong cold source on the Qinghai-Tibet Plateau, on the east-west vertical section along 30◦ N in Sichuan-Chongqing area Qinghai-Tibet Plateau, on the east-west vertical section along 30° N in Sichuan-Chongqing area (103°– (103–108◦ E) (upper left Figure9), there was an unusually strong “inversion cover”. Moreover, the108° continuously E) (upper left downward Figure flow9), there below was 700 an hPa un alongusually the mountainstrong “inversion inhibited thecover”. vertical Moreover, diffusion the of localcontinuously pollutants. downward However, flow in weak below years 700 hPa (upper along right the Figure mountain9), there inhibited was abnormal the vertical easterly diffusion uplift of airflowlocal pollutants. in Sichuan-Chongqing However, in weak regions, years and (upper abnormal right Figure warm near-ground9), there was temperature,abnormal easterly which uplift was conducive to strengthening the uplift movement. On the vertical section in the south-north direction of Sichuan-Chongqing area (28–33◦ N) along 105◦ E, there was also an abnormally strong “inversion cover” in the year of the strong cold source (lower left Figure9). Moreover, there was a consistent downward flow below 700 hPa, which inhibited the uplift and diffusion and was conducive to the accumulation of pollutants. However, in weak years (lower right Figure9), there was abnormal southward uplift flow at 700 hPa and the abnormal warm near-ground temperature was conducive to strengthening uplift movement and reducing pollution. Atmosphere 2019, 10, x FOR PEER REVIEW 12 of 17 airflow in Sichuan-Chongqing regions, and abnormal warm near-ground temperature, which was conducive to strengthening the uplift movement. On the vertical section in the south-north direction of Sichuan-Chongqing area (28°–33° N) along 105° E, there was also an abnormally strong “inversion cover” in the year of the strong cold source (lower left Figure 9). Moreover, there was a consistent downward flow below 700 hPa, which inhibited the uplift and diffusion and was conducive to the accumulation of pollutants. However, in weak years (lower right Figure 9), there was abnormal southward uplift flow at 700 hPa and the abnormal warm near-ground temperature was conducive to strengthening uplift movement and Atmosphere 2020, 11, 50 12 of 17 reducing pollution.

Figure 9. Circulation and temperature fields in east-west (top) and north-south (bottom) cross-section Figure 9. Circulation and temperature fields in east-west (top) and north-south (bottom) cross-section of the Sichuan-Chongqing region in strong (left) and weak (right) cold source years on the of the Sichuan-Chongqing region in strong (left) and weak (right) cold source years on the Qinghai- Qinghai-Tibet plateau. Tibet plateau. (5) Pearl River Delta Region (5) Pearl River Delta Region In the Pearl River Delta region, PM2.5 concentration was negatively correlated with the apparent In the Pearl River Delta region, PM2.5 concentration was negatively correlated with the apparent heat source Q1 on the Qinghai-Tibet Plateau. On the east-west vertical section of the Pearl River Delta heat source Q1 on the Qinghai-Tibet Plateau. On the east-west vertical section of the Pearl River Delta region (110–116◦ E) along 22.5◦ N, when the cold source was strong (upper left Figure 10), there was anregion abnormal (110°–116° “inversion E) along cover”, 22.5° N, which when was the conducivecold source to was inhibiting strong (upper vertical left movement. Figure 10), Moreover,there was therean abnormal was a west “inversion downward cover”, flow, which causing was the conduc transportationive to inhibiting of pollutants vertical from movement. the west Moreover, region to thethere Pearl was River a west Delta downward and accumulated flow, causing locally, the resultingtransportation in increased of pollutants pollution. from In the cold west source region weak to yearsthe Pearl (upper River right Delta Figure and 10accumulated), there was locally, ascending resulting airflow in fromincreased east to pollution. west in the In cold Pearl source River Deltaweak region,years (upper and the right temperature Figure 10), in there the lower was ascending layer was ai abnormallyrflow from high, east to thus west enhancing in the Pearl the upliftRiver Delta effect andregion, causing and the less temperature pollution. in the lower layer was abnormally high, thus enhancing the uplift effect and causing less pollution. On the vertical section along 112.5◦ E in the south-north direction of the Pearl River Delta region On the vertical section along 112.5° E in the south-north direction of the Pearl River Delta region (21–25◦ N), there was also an unusually strong “inversion cover” in the year of the strong cold source (lower(21°–25° left N), Figure there 10was), andalso therean unusua werelly weak strong southerly “inversion airflow cover” at low in the latitude year of and the northerly strong cold airflow source at high(lower latitude left Figure converging 10), and and there sinking were weak in the southerly north-south airflow direction, at low which latitude was and conducive northerly to airflow pollutant at accumulationhigh latitude converging and aggravated and sinking pollution. in Inthe cold north- sourcesouth weak direction, years (lowerwhich rightwas conducive Figure 10), to there pollutant was a clean southerly airflow from the ocean surface, which transported pollutants to the north, causing the pollution to weaken. Therefore, the pollution in the Pearl River Delta region was light in weak cold source years. Atmosphere 2019, 10, x FOR PEER REVIEW 13 of 17

accumulation and aggravated pollution. In cold source weak years (lower right Figure 10), there was a clean southerly airflow from the ocean surface, which transported pollutants to the north, causing

Atmospherethe pollution2020, 11to, 50weaken. Therefore, the pollution in the Pearl River Delta region was light in13 weak of 17 cold source years.

Figure 10. Circulation and temperature ﬁelds in the east-west (top) and north-south (bottom) cross-sectionFigure 10. Circulation of the Pearl and Rivertemperature Delta regionfields in in the strong east-west (left) ( andtop) weakand north-south (right) cold (bottom source) cross- years onsection the Qinghai-Tibet of the Pearl River plateau. Delta region in strong (left) and weak (right) cold source years on the Qinghai-Tibet plateau. 3.3. Spatial Distribution of Correlation between the Apparent Heat Source Q1 on Qinghai-Tibet Plateau and Haze Days in China and The Diﬀerence between the Two Sides of the Boundary Line 3.3. Spatial Distribution of Correlation between the Apparent Heat Source Q1 on Qinghai-Tibet Plateau and

HazeHaze Days datain China had and a longThe Difference time series between from the 1954 Two to Sides 2017, of thus the Boundary the correlation Line between Q1 on the Qinghai-Tibet plateau and air pollution in China, especially in typical regions, was analyzed by Haze data had a long time series from 1954 to 2017, thus the correlation between Q1 on the usingQinghai-Tibet long time plateau series and haze air data. pollution First, in the China, haze espe dayscially in December in typical from regions, 1954 was to 2017analyzed were by treated using bylong subtracting time series the haze national data. indexFirst, the trend haze value days for in many December years from to ignore 1954 theto 2017 impact were of increasingtreated by anthropogenicsubtracting the emissions, national index and then trend the value correlation for ma analysisny years was to madeignore betweenthe impact the hazeof increasing days in Chinaanthropogenic and the apparentemissions, heat and source then theQ1 correlationon the Qinghai-Tibet analysis was Plateau made inbetween the same theperiod. haze days The in spatial China distribution of correlation between the apparent heat source Q and haze days are shown in Figure 11. and the apparent heat source Q1 on the Qinghai-Tibet Plateau1 in the same period. The spatial It can be seen from Figure 11 that there existed an obvious northeast-southwest boundary line across distribution of correlation between the apparent heat source Q1 and haze days are shown in Figure the11. country.It can be On seen the from southeast Figure area 11 of that the there boundary, existed there an wasobvious mainly northeast-southwest a negative correlation, boundary with strong line coldacross sources the country. and more On haze the southeast days, while area on of the the northwest boundary, region there of was the boundarymainly a negative and northeast correlation, China, therewith wasstrong mainly cold asources positive and correlation, more haze with days, strong while cold on sourcesthe northwest and fewer region haze of days. the boundary and northeastThree China, section there lines was were mainly selected a positive in Figure correlation, 11, namely, with strong Section cold line sources 1: alongand fewer (92.5 haze◦ E, 37.5days.◦ N)–(120 ◦ E, 17.5◦ N) northwest-southeast direction; Section line 2: along (95◦ E, 45◦ N)–(127.5◦ E, 27.5◦ThreeN) northwest-southeast section lines were selected section line;in Figure Section 11, linenamely, 3: along Section (122.5 line◦ E,1: 50along◦ N)–(100 (92.5°◦ E,E, 37.5° 17.5◦ N)–N) northwest-southeast(120° E, 17.5° N) northwest-southeast direction. Section direction; line 1 and Section Section line 2: 3 intersectsalong (95° near E, 45° Guiyang N)–(127.5° (106 ◦E,E, 27.5° 27◦ N),N) andnorthwest-southeast Section line 2 intersects section Section line; Section line 3 nearline 3: Jincheng along (122.5° (112.66 E,◦ E,50° 35.5 N)–(100°◦ N). E, 17.5° N) northwest-

Atmosphere 2019, 10, x FOR PEER REVIEW 14 of 17

southeast direction. Section line 1 and Section line 3 intersects near Guiyang (106° E, 27° N), and Atmosphere 2020, 11, 50 14 of 17 Section line 2 intersects Section line 3 near Jincheng (112.66° E, 35.5° N).

FigureFigure 11. 11.Spatial Spatial correlationcorrelation distributions distributions and and proﬁle profile diagram diagram between between the the apparent apparent heat heat source sourceQ Q1 1 onon Qinghai-Tibet Qinghai-Tibet plateau plateau and and the the haze haze days days in in China. China.

VerticalVertical profiles profiles of of wind wind and and temperature temperature field field were were made made along along Section Section lines lines 1 1 and and 2 2 to to analyze analyze thethe influence influence mechanism mechanism ofof di differentfferent pollution pollution conditions conditionson on both both sides sides of of the the northeast-southwest northeast-southwest boundaryboundary line line (Figure (Figure 12 12).). OnOn the the northwest-southeast northwest-southeast section section (92.5 (92.5°◦ E, 37.5 E, ◦37N)–(120.5° N)–(120°◦ E, 17.5 E,◦ 17.5°N) (upper N) (upper Figure Figure12), in strong12), in coldstrong source cold years, source the years, northwest the northwest region of region 106◦ E of boundary 106° E boundary was a consistent was a consistent southeast southeast updraft, andupdraft, due toand topographic due to topographic reasons, the reasons, temperature the oftemperature the near-surface of the layer near-surface was warmer, layer thus was strengthening warmer, thus the upwardstrengthening movement, the upward which wasmovement, conducive which to the was diff conduciveusion of pollution. to the diffusion While theof pollution. southeast While region the of boundarysoutheast about region 106–114 of boundary◦ E corresponding about 106–114° to Guizhou, E corresponding Guangxi, to and Guizhou, Guangdong Guangxi, areas, and the Guangdong lower layer wasareas, a northwest the lower downwardlayer was a flow, northwest and the downward temperature flow, was and abnormally the temperature low, which was was abnormally conducive low, to inhibiting convection–diffusion and aggravating pollution. In Q weak years, the northwest region of which was conducive to inhibiting convection–diffusion and aggravating1 pollution. In Q1 weak years, thethe 106 northwest◦ E boundary, region such of asthe northwest 106° E boundary, Guizhou and such Sichuan, as northwest was a consistent Guizhou northwest and Sichuan, downward was a flow,consistent which northwest inhibiteduplift downward and di ffflow,usion. which However, inhibi thereted uplift was uplifted and diffusion. airflow atHowever, the lower there layers was of Guangxiuplifted andairflow Guangdong at the lower in the layers southeast of Guangxi regions and of boundaryGuangdong and in the the temperature southeast regions of the near-surfaceof boundary layerand the was temperature abnormally warm,of the whichnear-surface was conducive layer was to abnormally strengthening warm, the upliftingwhich was movement conducive and to reducingstrengthening pollution. the uplifting movement and reducing pollution. OnOn thethe northwest-southeastnorthwest-southeast sectionsection (95(95°◦ E, 45° 45◦ NN to to 127.5° 127.5◦ E,E, 27.5° 27.5 ◦N)N) along along the the boundary boundary line line of of111° 111 E◦ E(bottom (bottom Figure Figure 12), 12), in in the the strong strong cold cold source years, the oceanocean surfacesurface temperaturetemperature waswas abnormallyabnormally warm,warm, withwith updraftupdraft reachingreaching 850–700850–700 hPahPa andand transferringtransferring toto southerlysoutherly airflowairflow toto thethe northwest.northwest. AfterAfter encounteringencountering northerlynortherly downwarddownward flowflow fromfrom thethe northnorth nearnear111 111°◦ E Eregion, region,it itsinks sinks inin Henan,Henan, Anhui,Anhui, Jiangsu,Jiangsu, Shanghai,Shanghai, andand ZhejiangZhejiang regionsregions southeastsoutheast ofof thethe boundaryboundary lineline andand thethe underlyingunderlying horizontalhorizontal windwind waswas weak,weak, whichwhich waswas conduciveconducive toto pollutant pollutant accumulation.accumulation. However,However, inin weak weak years, years, the the southeast southeast area area of of the the boundary boundary was was consistent consistentwith with thetheascending ascending airflow,airflow, which which waswas conduciveconducive toto verticalvertical didiffusion.ffusion. AndAnd inin thethe northwestnorthwest regionregion ofof thethe boundary,boundary, itit waswas changedchanged fromfrom the the slight slight southerly southerly updraftupdraft alongalong thethe terrainterrain toto thethe downwarddownward flow,flow, and and the the abnormal abnormal warm warm temperaturetemperature in in the the lower lower layer layer was was conducive conducive to strengthening to strengthening the subsidence the subsidence of the airflow, of the resulting airflow, inresulting the accumulation in the accumulation of pollution of inpollution the northwest in the northwest region. region.

Atmosphere 2020, 11, 50 15 of 17 Atmosphere 2019, 10, x FOR PEER REVIEW 15 of 17

Figure 12. Circulation and temperature fields on the northwest-southeast section line 1 (top) and line 2 Figure 12. Circulation and temperature fields on the northwest-southeast section line 1 (top) and line (bottom) in strong and weak Q1 years. 2 (bottom) in strong and weak Q1 years. Therefore, when the cold source was strong, the pollution in the northwest region of the dividing line wasTherefore, light, while when thethe pollutioncold source in was the strong, southeast the regionpollution was in heavy. the northwest And it wasregion just of the the oppositedividing whenline was the light, cold sourcewhile wasthe pollution weak. in the southeast region was heavy. And it was just the opposite when the cold source was weak. 4. Summaries and Discussions 4. Summaries and Discussions The spatial distribution of correlation between the apparent heat source Q1 on the Qinghai-Tibet PlateauThe and spatial PM2.5 distributionconcentration of correlation in Chinahas between a northeast-southwest the apparent heat boundary, source Q1 andon the it hasQinghai-Tibet a negative correlationPlateau and in PM the2.5 southeast concentration region, in which China is has when a northeast-so the cold sourceuthwest is strong, boundary, the pollution and it has in thisa negative area is heavy.correlation However, in the itsoutheast has a positive region, correlation which is when in the the northwest cold source region, is strong, which the is when pollution the coldin this source area isis strong,heavy. However, the pollution it has is a light. positive In the correlation Beijing-Tianjin-Hebei in the northwest and region, Fen-Wei which regions, is when there the is cold a positive source correlationis strong, the between pollutionQ1 isand light. PM In2.5 theconcentration Beijing-Tianjin-Hebei while in Yangtze and Fen-Wei River Delta, regions, Sichuan-Chongqing, there is a positive andcorrelation Pearl River between Delta Q regions,1 and PM there2.5 concentration is a negative correlation.while in Yangtze River Delta, Sichuan-Chongqing, and PearlCompared River withDelta PMregions,2.5, the there haze is dataa negative have acorrelation. long time series (1954–present). Analysis of the correlationCompared between with hazePM2.5 and, theQ haze1 shows data that have the a spatiallong time distribution series (1954–present). has similar characteristics Analysis of the to PMcorrelation2.5, with abetween northeast-southwest haze and Q1 boundaryshows that line, the with spatial a positive distributi correlationon has tosimilar the north characteristics and negative to correlationPM2.5, with toa northeast-southwest the south of the boundary boundary line. line, with a positive correlation to the north and negative correlationThe comparative to the south analysis of the boundary of the circulation line. field and temperature field in different Q1 shows that in theThe strong comparative cold source, analysis northerly of the winds circulation strengthen field inand the temperature middle and field high in latitudes, different and Q1 thereshows has that a northerlyin the strong sinking cold airflowsource, northerly in the southeast winds regionstrength suppressingen in the middle convection and high and latitudes, diffusion, and resulting there has in increaseda northerly pollution. sinking airflow However, in therethe southeast exists a risingregion airflow, suppressing which convection reduced pollution and diffusion, in the northwest resulting region.in increased When pollution. the cold source However, is weak, there the situationexists a rising is just theairflow, opposite. which reduced pollution in the northwestIn the region. cold source When weak the year,cold source the geopotential is weak, the height situation over theis just Bay the of Bengalopposite. at 500 hPa decreases, correspondingIn the cold to source the deepening weak year, of the the geopotential southern branch heig channel,ht over the leading Bay of the Bengal 850 hPa at 500 southerly hPa decreases, airflow tocorresponding the north, which to the changes deepening to the of southerly the southern airflow branch due to thechannel, influence leading of plateau the 850 topography hPa southerly and airflow to the north, which changes to the southerly airflow due to the influence of plateau topography and merges with the easterly airflow in North China at about 35° N, while the northwest

Atmosphere 2020, 11, 50 16 of 17

merges with the easterly airflow in North China at about 35◦ N, while the northwest area has abnormal downward flow, thus aggravating the pollution. When the cold source increases, the abnormal westerly jet at 200 hPa appears over the Qinghai-Tibet Plateau to Qinghai, the East Asian trough at 500 hPa deepens, the Siberian high on the ground increases, the northerly winds at mid-high latitudes strengthen, and the downward flow at the southeast region has an abnormal northerly, thus inhibiting the convection–diffusion, causing the pollution to increase. Analysis of the circulation situation shows that the thermal effect of the Qinghai-Tibet Plateau has an important influence on the atmospheric circulation in the plateau, its surrounding areas and downstream areas. In the year of strong heating of the Qinghai-Tibet Plateau, the upward movement, convergence of the lower layer and divergence of the upper layer in the plateau and its adjacent areas are enhanced, and the suction effect of the plateau heating on the surrounding lower layer air and the emission effect of the upper atmosphere to the surrounding areas are enhanced, and vice versa. The thermal effect of the Qinghai-Tibet Plateau can affect the atmospheric circulation field in its surrounding and downstream areas, thus affecting the atmospheric pollution in the surrounding and downstream areas, and the effects on the atmospheric pollution in different areas are different. Through correlation analysis of the winter heat source Q1 on the Qinghai-Tibet Plateau and the PM2.5 concentration data of 902 stations in China in the past 5 years, as well as correlation analysis of the haze data of Q1 and 2444 stations in China since 1958, it is shown that there is a northeast-southwest boundary line in China. In the southeast region of the boundary line, Q1 is negatively correlated with pollution and positively correlated in the northwest region of the boundary line. The thermal effects of the Qinghai-Tibet Plateau have different impacts on the atmospheric circulation in different regions, therefore, Q1 is positively correlated with air pollution in the Beijing-Tianjin-Hebei and Fen-Wei Plain areas located in the northwest region of the dividing line, while the Yangtze River Delta, Sichuan-Chongqing, and Pearl River Delta areas located in the southeast region of the dividing line are mainly negatively correlated. Based on the observation data, we preliminarily discuss the influence of the change of the Q1 on the Qinghai-Tibet plateau on the atmospheric circulation and meteorological conditions in different typical regions of China, and it also potentially affects the increase of air pollution events in China. In recent years, the Chinese government has taken many important measures and made great progress in reducing emissions and air pollution. However, China’s unique and complex geographical distribution may affect the effectiveness of China’s air pollution control measures. Therefore, we have identified and discussed major pollution areas in China, and the role of thermal variability on the Qinghai-Tibet plateau may be taken into account when planning the location of new industrial facilities for China’s future development, thus as to prioritize the reduction of anthropogenic emissions in vulnerable areas, thereby reducing the number and severity of air pollution events. Subsequent research needs to collect PM2.5 concentration data from more monitoring stations in a longer time series and by means of high-precision simulation and sensitivity tests of numerical models, thus as to deeply explore how the thermal effects of the Qinghai-Tibet Plateau affect the atmospheric pollution in the surrounding and downstream areas, and how the strong and weak years of the thermal effects of the Qinghai-Tibet Plateau affect the atmospheric circulation and the atmospheric pollution in different regions in China.

Author Contributions: Conceptualization, X.A.; methodology, C.W. and Y.Z.; software, Y.L.; validation, Y.L.; formal analysis, Y.L.; resources, C.W. and Y.L.; data curation, C.W. and Y.L.; writing—original draft preparation, Y.L.; writing—review and editing, X.A.; supervision, G.F. and J.L.; project administration, X.A.; funding acquisition, X.A. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the National Natural Science Foundation of China (grant numbers 91644223), China; the National Natural Science Foundation of China (grant numbers 41975173), China. Conﬂicts of Interest: The authors declare no conﬂict of interest. Atmosphere 2020, 11, 50 17 of 17

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