Latest observations of total gaseous mercury in a megacity (Lanzhou) in northwest China

Journal Pre-proof Latest observations of total gaseous mercury in a megacity (Lanzhou) in northwest China

Xiufeng Yin, Wenting Zhou, Shichang Kang, Benjamin de Foy, Ye Yu, Jin Xie, Shiwei Sun, Kunpeng Wu, Qianggong Zhang PII:

S0048-9697(20)31005-6

DOI:

https://doi.org/10.1016/j.scitotenv.2020.137494

Reference:

STOTEN 137494

To appear in:

Science of the Total Environment

Received date:

18 November 2019

Revised date:

20 February 2020

Accepted date:

20 February 2020

Please cite this article as: X. Yin, W. Zhou, S. Kang, et al., Latest observations of total gaseous mercury in a megacity (Lanzhou) in northwest China, Science of the Total Environment (2018), https://doi.org/10.1016/j.scitotenv.2020.137494

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© 2018 Published by Elsevier.

Journal Pre-proof

Latest observations of total gaseous mercury in a megacity (Lanzhou) in northwest China Xiufeng Yin 1, 2, 3, Wenting Zhou 1, Shichang Kang 1, 3, 4, Benjamin de Foy 5, Ye Yu 6, Jin Xie 7, Shiwei Sun1, 3, Kunpeng Wu 8, Qianggong Zhang 2, 4 1

State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of

Science, Lanzhou, 730000, China 2

Academy of Sciences, Beijing, 100101, China 3

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University of Chinese Academy of Sciences, Beijing, 100039, China

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Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese

4

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CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100085, China

5

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Department of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO, 63108, USA

6

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Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute

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of Eco-Environment and Resources, Chinese Academy of Science, Lanzhou 730000, China 7

China Meteorological Administration, National Meteorological Center, Beijing, 100081, China

8

Correspondence

to:

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Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650091, China

Qianggong

Zhang

([email protected])

and

Shichang

Kang

([email protected])

Abstract One year of online Total Gaseous Mercury (TGM) measurements were carried out for the first time in Lanzhou, a city in northwest China that was once seriously polluted. Measurements were made from October 2016 to October 1

Pre-proof 2017 using the Tekran 2537B instrument, andJournal the annual mean concentration of TGM in Lanzhou was 4.48 ± 2.32 ng m-3 (mean ± standard deviation). TGM concentrations decreased during the measurement period, with autumn 2017 average concentrations 2.87 ng m-3 lower than autumn 2016 average concentrations. Similar diurnal variations of TGM were obtained in different seasons with low concentrations observed in the afternoon and high concentrations at night. The principal component analysis and conditional probability function results revealed that the sources of mercury were similar to the other atmospheric pollutants such as SO2, CO, NO2 and PM2.5, and were mainly from industrial combustion plants in urban districts. Concentration weighted trajectory analysis using backward trajectories

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demonstrated that higher mercury concentrations were related to air masses from adjacent regions, indicating the

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importance of influences from local-to-regional scale sources. A synthesis of multi-decadal atmospheric mercury

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measurements in Lanzhou and other Chinese megacities revealed that atmospheric mercury concentrations were either

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generally stable or experienced a slight decrease, during a time when China implemented control measures on

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atmospheric pollution. Long-term atmospheric mercury observations in urban and background sites in China are

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warranted to assess mercury pollution and the effectiveness of China’s mercury control policies.

1 Introduction

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Keywords: total gaseous mercury, observation, temporal variation, potential sources, pollution control

Mercury (Hg) is a pollutant that has significant impacts on human health and the environment globally because of its toxicity, bioaccumulation, long-range transport and persistence. The majority of the mercury released to the environment is released into the atmosphere from emission sources and is transported by air masses around the earth. Atmospheric mercury is composed of Total Gaseous Mercury (TGM) and Particle-Bound Mercury (PBM or Hg-p). TGM can be further divided into two forms: Gaseous Elemental Mercury (GEM) and Reactive Gaseous Mercury (RGM). Approximately 95–100% of atmospheric mercury exists in the form of GEM. The global residence time of 2

Pre-proof GEM is about 0.5-2 years due to its chemicalJournal characteristics, such as high volatility, high chemical stability and low solubility in the lower atmosphere (Schroeder and Munthe, 1998; Shia et al., 1999). This gives it the ability to be transported from the pollution sources over long distances. There is a small but measurable amount of RGM in TGM, and RGM has a relatively short lifetime of about a few days (Valente et al., 2007). GEM is oxidized into RGM by reactions with oxidants (Holmes et al., 2010). Conversely, RGM can be transformed into GEM via reduction with SO32- (aq) or SO2 (g), and RGM can be converted to PBM upon adsorption/absorption on aerosol surfaces (Lindberg and Stratton, 1998).

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The anthropogenic emissions of mercury in China are the largest in the world, and most of the mercury emissions

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in China originated from coal combustion, cement production, iron and steel production and non-ferrous smelting

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production (Pacyna et al, 2008; Wang et al., 2014; AMAP/UNEP, 2013). In recent decades, atmospheric mercury has

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been studied in eastern and central China (Liu et al., 2002; Fang et al., 2004; Xiang and Liu, 2008; Fu et al., 2012a; Fu

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et al., 2012b; Chen et al., 2013; Zhang et al., 2015), and the concentrations of atmospheric mercury over eastern and central China were found to be higher than the worldwide mean level measured at background sites (Sprovieri et al.,

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2016). Furthermore, automatic continuous measurements of atmospheric mercury in northwest China were reported

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from two background sites on the Tibetan Plateau: Waliguan and Nam Co with mean TGM concentrations of 1.98 ± 0.98 ng m-3 and 1.33 ± 0.24 ng m-3, respectively (Fu et al., 2012a; Yin et al., 2018). However, research on atmospheric mercury is still lacking in cities in northwest China. Lanzhou was one of the most air-polluted cities in China over the past few decades due to its narrow river valley topography and industrial emissions. In 2003-2004, a total of 20 manual samples of atmospheric mercury were analyzed by AMA254 (Advanced Mercury Analyser 254, Milestone, Italy) in Lanzhou, and results revealed an average concentration of 28.62 ng m-3 (48.48 ng m-3 in heating seasons and 9.42 ng m-3 in non-heating seasons), representing one of the highest atmospheric mercury level reported for China’s big cities (Su et al., 2007). In the past decade, with the implementation of corresponding air pollution control measures (e.g. reducing the use of coal for both industry and 3

Journal Pre-proof residents, closing and suspending polluting enterprises ), Lanzhou’s air quality has largely improved (Zhao et al., 2018), and Lanzhou won the award for Today’s Transformative Step 2015 at the World Climate Conference due to the innovative measures and notable achievements in air pollution control. As a result, it is necessary to update the understanding of atmospheric mercury in Lanzhou and northwest China. In this study, continuous measurements of high-time resolution TGM were conducted for the first time in Lanzhou. Meteorological and air quality data, principal component analysis, conditional probability function, backward trajectories and concentration weighted trajectory were used to identify the temporal variations, long-range transport

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impacts and potential sources of TGM in Lanzhou. In addition, a brief synthesis of multi-decadal changes in

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atmospheric mercury in China’s mega cities and the potential linkage to mercury pollution control were also

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conducted.

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2 Material and Methods

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2.1 Measurement site

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Lanzhou is the largest city and capital of Gansu Province in northwest China, and it is located along the Yellow River (Fig. 1) and has a big area of 10 000 km2 and a large population of 4 million. Lanzhou is situated in a temperate

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zone and has a semi-arid climate that features cold and dry winters and hot summers. TGM measurements were conducted at the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (36.05° N, 103.858° E; 1540 m a.s.l.) in Lanzhou starting on October 21, 2016, until October 7, 2017. Instruments were checked and a monitoring log file was created each week by instrument operators. Measurements were interrupted intermittently to carry out equipment maintenance. All data used in this study are reported in Beijing Time (China Standard Time, UTC+8). Solar noon in Lanzhou occurs at 13:04 Beijing Time. 2.2 TGM, air quality and meteorological measurements TGM concentration measurements were taken with a Tekran model 2537 B instrument (Tekran Instruments Corp., Toronto, Ontario, Canada), which was installed on the top floor of building No. 1 (an eight-story building) at the 4

Northwest Institute of Eco-Environment and Journal Resources, Pre-proof Chinese Academy of Sciences in the downtown. In recent decades, the Tekran 2537 analyzer has been used in most studies of TGM/GEM worldwide (Lyman et al., 2019). Ambient air (sample air) was introduced from an inlet 30 m above ground using a 45-mm diameter Teflon filter with a pore size of 0.2 μm that was in front of the inlet. The air represented the mixed concentration of downtown surface air. The Tekran 2537 B uses the amalgamation of mercury onto dual gold cartridges, from which continuous measurements of atmospheric mercury can be obtained. The amalgamated mercury was thermally desorbed into an argon carrier gas stream and analyzed using an internal detector that used cold vapor atomic fluorescence spectrophotometry (λ=253.7

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nm) (Landis et al., 2002). The sampling interval was 5 min, and the sampling flow rate was 0.8 L min-1 (at standard

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temperature and pressure). The Tekran model 2537 B instrument in this study provided TGM analysis at sub-ng m-3

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levels, with a detection limit < 0.1 ng m−3. In addition to the automatic calibration every 25 h using an internal

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permeation source in Tekran 2537 B, the measurement accuracy was estimated using manual injection calibration

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every 3 months and was found to be higher than 95 %.

Measurements of temperature (T), relative humidity (RH), wind speed (WS) and wind direction (WD) were

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conducted in Lanzhou by a local automatic meteorological station system. The air-quality data, including AQI (air

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quality index), SO2, NO2, CO, O3, PM2.5 and PM10, were obtained from the state-controlled site of the China National Environmental Monitoring Center (http://106.37.208.233:20035/, last access: October 2018). The air quality monitoring site (36.0464° N, 103.831° E; 1531 m a.s.l.) is 2.5 km southwest of the TGM monitoring site. Details of the air pollutants data information are available in Yin et al. (2019). 2.3 Conditional probability function (CPF) The CPF was applied in this study to identify the directions of atmospheric mercury sources to the site by openair package in R (Carslaw and Ropkins, 2012). The CPF estimates the probability that a given source contributing mercury from a given wind direction will exceed a predetermined threshold criterion. The CPF is defined as: 𝐶𝑃𝐹Δ𝜃 =

mΔ𝜃 nΔ𝜃

5

(4)

Pre-proof where mΔθ is the number of occurrences Journal from wind sector Δθ that exceeded the threshold criterion, and nΔθ is the total amount of data from the same wind sector (Carslaw and Ropkins, 2012). In this study, the probability that the TGM concentrations coming from a given wind sector (Δθ = 0.1°) exceed the mean concentration of TGM measured at the observation site was calculated. 2.4 Meteorological simulations and anthropogenic mercury emissions To identify the potential source of TGM in Lanzhou, backward trajectories and clusters were calculated by the NOAA HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) model (Draxler and Rolph, 2003,

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http://ready.arl.noaa.gov/HYSPLIT.php, last access: June 2019) using TrajStat (Wang et al., 2009), which is a free

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software plugin of MeteoInfo (Wang, 2014). Trajectories were calculated using the gridded meteorological data from

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the Global Data Assimilation System (GDAS-1) by the U.S. National Oceanic and Atmospheric Administration

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(NOAA) with 23 vertical levels from 1000 hPa to 20 hPa and a horizontal resolution of 1°×1° latitude and longitude

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(http: // www. arl. noaa. gov/ gdas1. php, last access: June 2019).

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Air masses that arrived in Lanzhou were calculated at different heights (500 m, 1000 m and 1500 m) above ground, and the results showed similar patterns for different heights in the HYSPLIT model. In this study, 500 m was

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selected as the arrival height in the HYSPLIT calculation to represent the air mass obtained by ground-monitoring of atmospheric mercury in the following analysis. This height was considered a suitable height for both the planetary boundary layer and long-range transport in Lanzhou. The hourly backward trajectory arrival height in the HYSPLIT model was set at 500 m above the surface in this study, and the total run times for each backward trajectory were 120 hours with 1 hour time interval. Angle distance was chosen to calculate clusters in the HYSPLIT calculation. Solar radiation downward (SWD), planetary boundary layer height (PBLH) and specific humidity (Q) data were obtained from WRF simulations. The emission inventory of anthropogenic mercury in China was provided by Wu et al. (2016). The emissions over other Asian countries were provided by the UNEP global anthropogenic emission inventory (AMAP/UNEP, 2013). These inventories were at a 0.5×0.5° horizontal resolution for the year 2010. 6

2.5 Concentration weighted trajectory Journal (CWT)

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The CWT simulation was based on backward trajectories obtained from the HYSPLIT model and the in-situ measurements to identify the potential pollutant sources to monitoring site. In this study, we calculated the CWT based on trajectories corresponding to concentrations that exceeded the mean level (4.48 ng m-3) of TGM. The resolution for CWT was 0.5°×0.5° in this study. In the CWT method (Hsu et al., 2003; Seibert et al., 1994), each grid cell is assigned a weighted concentration by averaging the sample concentrations with associated trajectories that crossed that grid cell as follows: ∑

𝐶

(1)

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=∑

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where Cij is the average weighted concentration in the ijth cell, l is the index of the trajectory, M is the total

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number of trajectories, Cl is the concentration observed upon arrival of trajectory l, and τijl is the time spent in the ijth

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cell by trajectory l. A high value of Cij implies that air parcels traveling over the ijth cell were thought to be, on

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average, associated with high concentrations at the receptor cell.

𝑁 > 3𝑁𝑎𝑣𝑒 3𝑁𝑎𝑣𝑒 > 𝑁 > 1.5𝑁𝑎𝑣𝑒 1.5𝑁𝑎𝑣𝑒 > 𝑁 > 𝑁𝑎𝑣𝑒 𝑁𝑎𝑣𝑒 > 𝑁

(2)

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1.00 0.70 𝑊 0.42 {0.05

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The weighting function was used in the CWT analyses to reduce the effect of small values of nij as:

where Wij represents the weight function and reflects the uncertainty of the values in each cell, Nij represents the number of endpoints that fall in the ij-th cell, and Nave represents the mean Nij of all grid cells. The weighted CWT result=Wij×CWT. 2.6 Principal component analysis (PCA) PCA was used for apportioning potential atmospheric mercury sources at many sites (Cheng et al., 2015). PCA was used in this study to compare the TGM, other atmospheric pollutants and meteorological parameters, allowing for the large number of parameters to be reduced to a smaller set of components to preliminarily identify the potential 7

Journal Pre-proof sources of TGM in Lanzhou. As described in Cheng et al. (2015), PCA is based on a mathematical model is as follows: =∑

(3)

Zij is the standardized observed concentration of the jth pollutant in the ith sample; Sik is the kth component score on the ith sample; Lkj is the component loading for each pollutant; k is the component; and P is the number of components. In this study, there are 16 input variables: TGM, SO2, CO, NO2, O3, O3_8h, PM2.5, PM10, AQI, T, WS, WD, Q, RH, PBLH and SWD. The data set is suitable for PCA, as the Kaiser–Meyer–Olkin measure of sampling adequacy is 0.766 and passes Bartlett’s test of sphericity (p < 0.05). Five factors were determined by Kaiser’s criterion

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(eigenvalues > 1, the elements in the diagonal of the variance-covariance matrix of the principal components are

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known as the eigenvalues.) and a Monte Carlo parallel analysis. Kaiser's varimax rotation was applied to the

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components in the final PCA solution.

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3.1 Overall TGM concentration

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3 Results and discussion

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The annual mean TGM concentration in Lanzhou was 4.48±2.32 ng m-3 (Fig. S1). The frequency distribution of the hourly mean TGM concentration in Lanzhou was a normal distribution (Fig. S2) and 96% of the hourly mean TGM

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concentrations in Lanzhou fell within the range of 1.5-9.5 ng m-3. The mean TGM concentration in Lanzhou was much higher than the annual mean concentration at background sites in the Northern Hemisphere (~1.5 ng m-3) (Sprovieri et al., 2016) and remote sites in China (Fig. 2). The mean concentration of TGM in Lanzhou was much higher than that in Waliguan (1.98±0.98 ng m-3), which is the nearest background site to Lanzhou, indicating the impacts of human activities in the city. TGM concentrations in Lanzhou were in the range of the concentrations measured in other urban sites in China (Table 1). In southwestern China, Guiyang was one of the cities with the earliest measurements of atmospheric mercury. The average concentration of TGM was reported in Guiyang as 8.4 ng m-3 in 2002 (Feng et al., 2004). Chongqing was another city in southwestern China that had TGM measurements, and the average concentration was 8

~7 ng m-3 from August 2006 to SeptemberJournal 2007 (YangPre-proof et al., 2009). Fang et al. (2004) measured the TGM in Changchun in northeastern China and reported that the average TGM concentration was 18.4 ng m-3 at the urban site. In Beijing, GEM concentrations ranged from 4.9 ng m-3 to 8.3 ng m-3 in different seasons (Wang et al., 2007). Duan et al. (2017) found the annual mean concentration of GEM in Shanghai was 4.19 ng m-3. Yu et al. (2016) measured GEM in both on non-haze and haze days and found concentrations of GEM on haze days were higher than those on non-haze days. Atmospheric mercury measurements were also obtained in central and eastern China, including Qingdao, Xiamen, Ningbo, Guangzhou, Jiaxing, Nanjing and Wuhan, with average TGM/GEM concentrations ranging from 2.7

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ng m-3 to 14.8 ng m-3 (Wang et al., 2007; Xiang et al., 2008; Friedli et al., 2011; Nguyen et al., 2011; Zhu et al., 2012;

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Chen et al., 2013; Zhang et al., 2014; Xu et al., 2015). According to previous studies at urban sites in China, the sites

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with TGM/GEM concentrations lower than Lanzhou were mostly in coastal cities, while sites with higher TGM/GEM

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concentrations are mostly in inland cities (Fig. 2), indicating that transport from cleaner marine air to coastal cities

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leads to lower TGM/GEM concentrations in coastal cities (Friedli et al., 2011).

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3.2 Seasonal and diurnal variations in TGM

The seasonal variation in TGM in Lanzhou was characterized in decreasing order: autumn 2016 (7.02±3.11 ng

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m-3) > winter 2016-2017 (5.06±2.45 ng m-3) > summer 2017 (4.45±2.10 ng m-3) > autumn 2017 (4.15±1.78 ng m-3) > spring 2017 (3.66±1.23 ng m-3) (Fig. 3), which was a different seasonal pattern from previous observations in China (Zhang et al., 2015; Fu et al., 2008; Fu et al., 2009; Fu et al., 2010; Fu et al., 2011; Fu et al., 2012c; Feng et al., 2004; Xu et al., 2015; Wan et al., 2009) and at most AMNet (Atmospheric Mercury Network) sites (Lan et al., 2012). The difference in concentration between autumn 2016 and spring 2017 was 3.36 ng m-3, which corresponded to 75% of the total mean TGM concentration in Lanzhou (4.48 ng m-3). Previous studies have discussed the TGM/CO ratio due to their homogeneity as they have a majority of the same anthropogenic sources, including coal combustion, iron and steel production and cement production. The overall mean TGM/CO ratio in Lanzhou was 4.86 (ng m-3/ppmv-1), which is lower than the ratio for mainland China (7.3 as reported 9

Journal in Fu et al., 2015b) with a correlation coefficient of TGM Pre-proof to CO of 0.28 in Lanzhou. In the winter, the monthly mean TGM/CO ratios in Lanzhou were even lower (2.61 in December, 3.15 in January and 3.02 in February) (Fig. 4), suggesting enhanced local sources of CO such as domestic coal combustion, forest fire and agricultural residual burning. The ratios of TGM/CO were higher in the warm season, possibly as a result of soil emissions which are characterized by limited CO emissions (Fu et al., 2015b). TGM concentrations in Lanzhou showed pronounced diurnal variations with a generally regular pattern in different months, demonstrating a typical urban-style cycle of atmospheric mercury (Fig. S3). In general, the

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concentrations of TGM were higher at night than during the daytime in different seasons (Fig. 5). An increase in TGM

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after sunset was found in all seasons (Fig. 5), and a decrease after sunrise was found in the spring and the summer. For

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all seasons, the minimum TGM concentrations were observed in the afternoon. The diurnal variation of TGM in

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Lanzhou was similar to that in previous studies in Xiamen and Hefei (Xu et al., 2015; Hong et al., 2016).

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It was obvious that NO2 and CO peaked during rush hours (8-10 am and 17-18 pm) in Lanzhou (Fig. S4), which

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was associated with gasoline-powered vehicle emissions. However, for TGM, there was no significant rush-hour effect. This was because the total mercury emissions from the combustion of gasoline were limited (Won et al., 2007;

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Conaway et al., 2005). O3 and solar radiation peaked in the afternoon in different seasons and might contribute to the decrease in TGM in the afternoon due to the transition from GEM to RGM with the formation of atmospheric oxidants, resulting in GEM depletion. The boundary layer height and wind speed also peaked in the afternoon (Fig. S5). A convective mixed boundary layer and high wind speed usually increased vertical mixing, and more fresh air masses were introduced to the ground from the upper layer, diluting TGM near the surface during the daytime, and generating decreased TGM concentrations (Yin et al., 2018; Liu et al., 2011; Lee et al., 1998). Conversely, the high concentration of TGM at night was probably due to the shallow nocturnal boundary layer, which trapped TGM near the surface after sunset and before sunrise and has been widely found at different sites (Liu et al., 2011; Lee et al., 1998). 3.3 PCA results 10

Journal Pre-proof The first five factors in PCA explained 20.03%, 18.89%, 16.30%, 11.26% and 9.35% of the total variance (Table 2), and TGM was mostly loaded on Factor 1, 2, and 5. Factor 1 explained approximately 20% of the total variance and was characterized by the positive loading of SO2, CO, NO2, PM2.5 and TGM, and negative loadings of O3-8h. This factor was dominated by SO2, CO and NO2, which are most likely indicative of combustion sources (e.g., coal combustion, industrial combustion, fossil fuel burning, biomass burning, waste incineration emissions and road traffic emission) (Cheng et al., 2015). Factor 2 was characterized by positive loadings of the PBLH, SWD, O3 and temperature, and negative loadings of relative humidity and TGM. For both Factor 1 and Factor 2, the anti-correlation

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between TGM and parameters including O3-8h, O3 and SWD probably indicated the presence of photochemical

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processing (Liu et al., 2019). In addition, results of Factor 2 revealed correlation between the diurnal variation of TGM

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and boundary layer mixing. Factor 5 was characterized by positive loadings of relative humidity, humidity, temperature

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and TGM, reflecting the seasonality of the annual data. The other 2 factors (Factor 3 and Factor 4) contained small

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loadings of mercury. Factor 3 was characterized by positive loadings of PM10, PM2.5 and AQI and nearly zero correlations with TGM, indicating a weak correlation between TGM and particulate pollutants. Factor 4 was

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characterized by positive loadings of wind speed, O3-8h, and weak negative loadings of TGM, reflecting the diffusion

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effect and long-range transport. Above all, the TGM variation in Lanzhou might be mainly affected by the similar anthropogenic sources of other air pollutants (e.g. SO2, CO, NO2 and PM2.5),and secondarily by photochemical processes and boundary layer mixing.

3.4 Implications of the CPF, HYSPLIT and CWT results The CPF results are shown in Fig. 6. Generally, high TGM concentrations were associated with low wind speeds, representing favorable conditions for the accumulation of atmospheric mercury from local emissions (e.g. coal-fired plants in Chengguan District to the west of the monitoring site) and/or regional long-range transport. High TGM concentrations

were also associated with relatively high wind speeds from the east and south, which likely resulted from nearby point emission sources such as cement plants and coal-fired plants (Fig. 1). Cluster analysis of backward trajectories 11

revealed 4 groups of clusters (Fig. 7), clusterJournal 1 and 4 hadPre-proof lower mean TGM concentrations and generally originated from farther west with higher starting heights. In contrast, cluster 2 and 3 had higher mean TGM concentrations (cluster 2: 5.11 ± 2.5 ng m-3; cluster 3: 4.76 ± 2.44 ng m-3) and were characterized by shorter pathways, lower starting heights and lower traveling heights. In addtion, cluster 2 and 3 accounted for 23.48% and 37.3% of all trajectories arriving at Lanzhou during the monitoring period, implying that the TGM at Lanzhou were mainly influenced by local-to-regional scale sources. CWT analysis based on HYSPLIT trajectories further identified potential source regions of TGM (Fig. 8), it is clear that Lanzhou and its peripheral areas showed moderate-to-high CWT values. In

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particular, these nearby regions displayed higher weights of CWT in the autumn and winter (Fig. S6), possibly

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resulting from enhanced mercury emissions from domestic heating in Lanzhou city and surroundings.

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3.5 Sharp decrease in TGM in China’s megacities and potential linkage to mercury pollution control

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In this study, one year continuous TGM measurements revealed a clear decrease of TGM in Lanzhou. It is

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interesting to compare TGM concentration in the autumn of 2017 (4.15±1.78 ng m-3) with those in the autumn of 2016

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(7.02±3.11 ng m-3) (Fig. 2). Similar trends were also found for CO, SO2 and NO2 (Fig. S1). Zhao et al. (2018) reported that the AQI, PM2.5, PM10 and SO2 gradually decreased from 2013 to 2016 in Lanzhou. Long-term TGM

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measurements in Lanzhou and China’s other cities remained sparse, and the available TGM/GEM data in China are not sufficient to conclude a long-term trend concentrations (Fu et al., 2015a). This problem is further exacerbated by the use of different instruments and methods in previous studies (Table S1). Nevertheless, a few studies have reported levels of atmospheric mercury in China’s megacities. A previous study reported 28.62 ng m-3 atmospheric mercury in Lanzhou in 2003-2004 (Su et al., 2007), much higher than the annual mean TGM concentration (4.48±2.32 ng m-3) in 2016-2017. In this study, we summarized measurements of atmospheric mercury in China’s megacities (Fig. 9). Generally, a stable level and even slight decreases of atmospheric mercury concentrations were observed (Fig. 9). As the largest emitter of atmospheric mercury in the world, China has been introducing a series of regulations and measures to reduce anthropogenic mercury emissions during the past decade. Since 2010, China has extensively 12

Pre-proof strengthened atmospheric emission standards,Journal including mercury as a targeted pollutant. In 2010, mercury emission standards were issued for the lead and zinc industry (GB 25466-2010) and for the copper, nickel, cobalt industry (GB 25467-2010); In 2015, the mercury emission standard for thermal power plants was included in China’s state-of-the-art National Emission Standard of Air Pollutants for Thermal Power Plants (GB 13223–2011). It should be noteworthy that considerable co-benefits in terms of reduced mercury emissions were achieved from the use of air pollution control devices for other atmospheric pollutants (e.g. SO2, NOx and CO). In 2017, Government actions were implemented in various industries to achieve the goal of the Air Pollution Prevention and Control Action Plan The

prevention

and

control

actions

in

this

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(http://www.gov.cn/zwgk/2013-09/12/content_2486773.htm).

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comprehensive and tough action plan included controlling coal consumption (under 65% by 2017), improving fuel

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quality, transforming coal-fired boiler to natural gas, using high-quality coal, and relocating heavy industry factories

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(e.g. Lanzhou petrochemical plants) away from the city. The implementation of all these policies greatly reduced

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anthropogenic atmospheric mercury emissions. For examples, Chen et al. (2013) found that the mercury emission from biomass burning decreased from 6.08 Mg to 5.12 Mg from 2000 to 2010. Wu et al. (2016) found that mercury emission

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decreased by at an average annual rate of 0.8% during 2008-2010.

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We argue that the stable level and even slight decreases in observed TGM concentrations of the metropolitan atmosphere and of anthropogenic emissions in China may demonstrate the effectiveness of mercury pollution control measures and policies in China. It should be acknowledged that the primary synthesis of decadal changes in mercury pollution in China’s urban atmosphere in this study remained quite coarse and uncertain, resulting from extreme paucity of long-term continuous observation of TGM in China’s cities. This also underlined the importance and urgency of long-term observation of atmospheric mercury at multiple sites. We suggest that atmospheric mercury observations in cities in different areas should be strengthened for assessment of changes in urban atmospheric mercury in response to declining anthropogenic emissions. Furthermore, background monitoring sites should also be included to establish a national atmospheric mercury observation system. These will serve as fundamental references 13

Journal Pre-proof to verify the effects of mercury emission control as well as to fulfill the reporting obligation of the Minamata Convention on mercury. 4 Conclusions We conducted TGM measurements in Lanzhou in northwestern China for one-year (October 2016 to October 2017). The mean TGM concentration was 4.48±2.32 ng m-3 during the whole measurement period. The relatively low TGM level in Lanzhou relative to inland urban sites, the decreased TGM since 2003-2004, and the reduction of other air pollutants, indicated the improvement of air quality in Lanzhou in recent years. TGM variations in Lanzhou were

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largely affected by anthropogenic sources (e.g., coal-fired plants and cement plants) in the city districts and nearby

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regions, as was the case for other air pollutants (e.g., SO2, CO, NO2 and PM2.5). Besides, photochemical processes and

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boundary layer mixing may also influence the variability of TGM. A clear decrease in atmospheric mercury

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concentrations in Lanzhou was found when compared to limited available monitoring data in the early 21st century. A

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primary synthesis of decadal changes in mercury levels in China’s urban atmosphere revealed a general stable level

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and even slight decrease in the past two decades, implying that mercury pollution control measures have been effective. Coordinated long-term observations of atmospheric mercury at urban and background sites are urged as part of

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national atmospheric mercury observation system, which will provide a sound basis for assessing mercury pollution as well as the effectiveness of mercury control policies in China.

Data availability. All the data presented in this paper can be made available for scientific purposes upon request to the corresponding authors (Qianggong Zhang ([email protected]) or Shichang Kang ([email protected])).

Acknowledgments This study was supported by the National Natural Science Foundation of China (41907328 and 41971080), the Strategic Priority Research Program of Chinese Academy of Sciences, Pan-Third Pole Environment Study for a Green 14

Pre-proof Silk Road (Pan-TPE) (XDA20040501), and Journal State Key Laboratory of Cryospheric Science (SKLCS-ZZ-2019 and SKLCS-OP-2019-07). Q. G. Zhang acknowledges financial support from the Youth Innovation Promotion Association of CAS (2016070). X.F. Yin acknowledges financial support from the CAS "Light of West China" Program. We acknowledge the China National Environmental Monitoring Center and the National Oceanic and Atmospheric Administration for providing the data.

References:

of

[1] AMAP/UNEP, 2013. Technical Background Report for the Global Mercury Assessment 2013. Arctic Monitoring and Assessment

ro

Programme.

-p

[2] Carslaw, D.C., Ropkins, K., 2012. Openair—an R package for air quality data analysis. Environmental Modelling & Software. 27,

re

52-61.

lP

[3] Chen, C., Wang, H., Zhang, W., Hu, D., Chen, L., Wang, X., 2013. High‐ resolution inventory of mercury emissions from biomass

12,248-212,256.

na

burning in China for 2000–2010 and a projection for 2020. Journal of Geophysical Research: Atmospheres. 118,

Jo ur

[4] Chen, L., Liu, M., Xu, Z., Fan, R., Tao, J., Chen, D., Zhang, D., Xie, D., Sun, J., 2013. Variation trends and influencing factors of total

gaseous mercury in the Pearl River Delta—A highly industrialised region in South China influenced by seasonal monsoons.

Atmospheric environment. 77, 757-766.

[5] Cheng, I., Xu, X., Zhang, L., 2015. Overview of receptor-based source apportionment studies for speciated atmospheric mercury.

Atmos. Chem. Phys. 15, 7877-7895.

[6] Ci, Z., Zhang, X., Wang, Z., Niu, Z., 2011. Atmospheric gaseous elemental mercury (GEM) over a coastal/rural site downwind of East

China: Temporal variation and long-range transport. Atmospheric Environment. 45, 2480-2487.

[7] Conaway, C.H., Mason, R.P., Steding, D.J., Russell Flegal, A., 2005. Estimate of mercury emission from gasoline and diesel fuel

consumption, San Francisco Bay area, California. Atmospheric Environment. 39, 101-105. 15

Journal Pre-proof [8] Dingyong, W., Xiaohua, L., Cheng, W., 1996. Preliminary Investigation on the Atmospheric Mercury in Chongqing [J]. Chongqing Environmental Science. 4.

[9] Dou, H.Y., Wang, S.X., Wang, L., Zhang, L., Hao, J.M., Characteristics of total gaseous mercury concentrations at a rural site of

Yangtze Delta, China.

[10] Draxler, R.R., Rolph, G., HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) model access via NOAA ARL

READY website (http://www. arl. noaa. gov/ready/hysplit4. html). NOAA Air Resources Laboratory, Silver Spring, in, Md,

2003.

of

[11] Duan, L., Wang, X., Wang, D., Duan, Y., Cheng, N., Xiu, G., 2017. Atmospheric mercury speciation in Shanghai, China. Science of

ro

The Total Environment. 578, 460-468.

-p

[12] Fang, F., Wang, Q., Li, J., 2004. Urban environmental mercury in Changchun, a metropolitan city in Northeastern China: source,

re

cycle, and fate. Science of the Total Environment. 330, 159-170.

lP

[13] Feng, X., Shang, L., Wang, S., Tang, S., Zheng, W., 2004. Temporal variation of total gaseous mercury in the air of Guiyang, China.

Journal of Geophysical Research: Atmospheres. 109.

na

[14] Friedli, H., Arellano Jr, A., Geng, F., Cai, C., Pan, L., 2011. Measurements of atmospheric mercury in Shanghai during September

Jo ur

2009. Atmospheric Chemistry and Physics. 11, 3781-3788.

[15] Fu, X., Feng, X., Dong, Z., Yin, R., Wang, J., Yang, Z., Zhang, H., 2010. Atmospheric gaseous elemental mercury (GEM)

concentrations and mercury depositions at a high-altitude mountain peak in south China. Atmospheric Chemistry and Physics.

10, 2425-2437.

[16] Fu, X., Feng, X., Liang, P., Zhang, H., Ji, J., Liu, P., 2012a. Temporal trend and sources of speciated atmospheric mercury at

Waliguan GAW station, Northwestern China. Atmospheric Chemistry and Physics. 12, 1951-1964.

[17] Fu, X., Feng, X., Qiu, G., Shang, L., Zhang, H., 2011. Speciated atmospheric mercury and its potential source in Guiyang, China.

Atmospheric environment. 45, 4205-4212.

[18] Fu, X., Feng, X., Shang, L., Wang, S., Zhang, H., 2012b. Two years of measurements of atmospheric total gaseous mercury (TGM) at

16

Journal Pre-proof a remote site in Mt. Changbai area, Northeastern China. Atmospheric Chemistry and Physics. 12, 4215-4226. [19] Fu, X., Feng, X., Sommar, J., Wang, S., 2012c. A review of studies on atmospheric mercury in China. Science of the Total

Environment. 421, 73-81.

[20] Fu, X., Feng, X., Wang, S., Rothenberg, S., Shang, L., Li, Z., Qiu, G., 2009. Temporal and spatial distributions of total gaseous

mercury concentrations in ambient air in a mountainous area in southwestern China: Implications for industrial and domestic

mercury emissions in remote areas in China. Science of the total environment. 407, 2306-2314.

[21] Fu, X., Feng, X., Zhu, W., Wang, S., Lu, J., 2008. Total gaseous mercury concentrations in ambient air in the eastern slope of Mt.

of

Gongga, South-Eastern fringe of the Tibetan plateau, China. Atmospheric Environment. 42, 970-979.

ro

[22] Fu, X., Zhang, H., Yu, B., Wang, X., Lin, C.-J., Feng, X., 2015a. Observations of atmospheric mercury in China: a critical review.

-p

Atmos. Chem. Phys. 15, 9455-9476.

re

[23] Fu, X.W., Zhang, H., Lin, C.J., Feng, X.B., Zhou, L.X., Fang, S.X., 2015b. Correlation slopes of GEM / CO, GEM /

lP

CO₂, and GEM / CH₄ and estimated mercury emissions in China, South Asia, the Indochinese

Peninsula, and Central Asia derived from observations in northwestern and southwestern China. Atmos. Chem. Phys. 15,

na

1013-1028.

Jo ur

[24] Holmes, C.D., Jacob, D.J., Corbitt, E.S., Mao, J., Yang, X., Talbot, R., Slemr, F., 2010. Global atmospheric model for mercury

including oxidation by bromine atoms. Atmospheric Chemistry and Physics. 10, 12037-12057.

[25] Hong, Q., Xie, Z., Liu, C., Wang, F., Xie, P., Kang, H., Xu, J., Wang, J., Wu, F., He, P., Mou, F., Fan, S., Dong, Y., Zhan, H., Yu, X.,

Chi, X., Liu, J., 2016. Speciated atmospheric mercury on haze and non-haze days in an inland city in China. Atmos. Chem.

Phys. 16, 13807-13821.

[26] Hsu, Y.-K., Holsen, T.M., Hopke, P.K., 2003. Comparison of hybrid receptor models to locate PCB sources in Chicago. Atmospheric

Environment. 37, 545-562.

[27] Lan, X., Talbot, R., Castro, M., Perry, K., Luke, W., 2012. Seasonal and diurnal variations of atmospheric mercury across the US

determined from AMNet monitoring data. Atmospheric Chemistry and Physics. 12, 10569.

17

[28] Landis, M.S., Stevens, R.K., Schaedlich, F., Journal Prestbo, E.M.,Pre-proof 2002. Development and characterization of an annular denuder

methodology for the measurement of divalent inorganic reactive gaseous mercury in ambient air. Environmental science &

technology. 36, 3000-3009.

[29] Lee, D.S., Dollard, G.J., Pepler, S., 1998. Gas-phase mercury in the atmosphere of the United Kingdom. Atmospheric Environment.

32, 855-864.

[30] Li, Z., Xia, C., Wang, X., Xiang, Y., Xie, Z., 2011. Total gaseous mercury in Pearl River Delta region, China during 2008 winter

period. Atmospheric Environment. 45, 834-838.

of

[31] Lindberg, S.a., Stratton, W., 1998. Atmospheric mercury speciation: concentrations and behavior of reactive gaseous mercury in

ro

ambient air. Environmental Science & Technology. 32, 49-57.

-p

[32] Liu, C., Fu, X., Zhang, H., Ming, L., Xu, H., Zhang, L., Feng, X., 2019. Sources and outflows of atmospheric mercury at Mt.

re

Changbai, northeastern China. Science of The Total Environment. 663, 275-284.

lP

[33] Liu, M., Chen, L., Xie, D., Sun, J., He, Q., Cai, L., Gao, Z., Zhang, Y., 2016. Monsoon-driven transport of atmospheric mercury to the

South China Sea from the Chinese mainland and Southeast Asia—Observation of gaseous elemental mercury at a background

na

station in South China. Environmental Science and Pollution Research. 23, 21631-21640.

Jo ur

[34] Liu, N., Qiu, G., Landis, M.S., Feng, X., Fu, X., Shang, L., 2011. Atmospheric mercury species measured in Guiyang, Guizhou

province, southwest China. Atmospheric Research. 100, 93-102.

[35] Liu, S., Nadim, F., Perkins, C., Carley, R.J., Hoag, G.E., Lin, Y., Chen, L., 2002. Atmospheric mercury monitoring survey in Beijing,

China. Chemosphere. 48, 97-107.

[36] Lyman, S.N., Cheng, I., Gratz, L.E., Weiss-Penzias, P., Zhang, L., 2019. An updated review of atmospheric mercury. Science of The

Total Environment.

135575.

[37] Nguyen, D.L., Kim, J.Y., Shim, S.-G., Zhang, X.-S., 2011. Ground and shipboard measurements of atmospheric gaseous elemental

mercury over the Yellow Sea region during 2007–2008. Atmospheric environment. 45, 253-260.

[38] Pacyna, J., Munthe, J., Wilson, S., Maxson, P., Sundseth, K., Pacyna, E., Harper, E., Kindbom, K., Wängberg, I., Panasiuk, D., 2008.

18

Journal Pre-proof Technical background report to the global atmospheric mercury assessment. Arctic Monitoring and Assessment Programme/UNEP Chemical Branch.

[39] Schroeder, W.H., Munthe, J., 1998. Atmospheric mercury—an overview. Atmospheric Environment. 32, 809-822.

[40] Seibert, P., Kromp-Kolb, H., Baltensperger, U., Jost, D., Schwikowski, M., Kasper, A., Puxbaum, H., 1994. Trajectory analysis of

aerosol measurements at high alpine sites. Transport and Transformation of Pollutants in the Troposphere. 689-693.

[41] Shia, R.L., Seigneur, C., Pai, P., Ko, M., Sze, N.D., 1999. Global simulation of atmospheric mercury concentrations and deposition

fluxes. Journal of Geophysical Research: Atmospheres. 104, 23747-23760.

of

[42] Sprovieri, F., Pirrone, N., Bencardino, M., D'Amore, F., Carbone, F., Cinnirella, S., Mannarino, V., Landis, M., Ebinghaus, R.,

ro

Weigelt, A., 2016. Atmospheric mercury concentrations observed at ground-based monitoring sites globally distributed in the

-p

framework of the GMOS network. Atmospheric Chemistry and Physics. 16, 11915-11935.

re

[43] Su, J., Cheng, J.-p., Ye, X., Yuan, T., Wang, W., Mi, L., 2007. Preliminary study on mercury distribution in multimedia environment

lP

in Lanzhou. Journal of Agro-Environment Science. 26, 381-385.

[44] Valente, R.J., Shea, C., Lynn Humes, K., Tanner, R.L., 2007. Atmospheric mercury in the Great Smoky Mountains compared to

na

regional and global levels. Atmospheric Environment. 41, 1861-1873.

Jo ur

[45] Wan, Q., Feng, X., Lu, J., Zheng, W., Song, X., Han, S., Xu, H., 2009. Atmospheric mercury in Changbai Mountain area,

northeastern China I. The seasonal distribution pattern of total gaseous mercury and its potential sources. Environmental

Research. 109, 201-206.

[46] Wang, S., Zhang, L., Wang, L., Wu, Q., Wang, F., Hao, J., 2014. A review of atmospheric mercury emissions, pollution and control

in China. Frontiers of Environmental Science & Engineering. 8, 631-649.

[47] Wang, Y., 2014. MeteoInfo: GIS software for meteorological data visualization and analysis. Meteorological Applications. 21,

360-368.

[48] Wang, Y., Zhang, X., Draxler, R.R., 2009. TrajStat: GIS-based software that uses various trajectory statistical analysis methods to

identify potential sources from long-term air pollution measurement data. Environmental Modelling & Software. 24, 938-939.

19

Pre-proof [49] Wang, Z.-w., Chen, Z.-s., Duan, N., Zhang, X.-s.,Journal 2007. Gaseous elemental mercury concentration in atmosphere at urban and remote sites in China. Journal of Environmental Sciences. 19, 176-180.

[50] Won, J.H., Park, J.Y., Lee, T.G., 2007. Mercury emissions from automobiles using gasoline, diesel, and LPG. Atmospheric

Environment. 41, 7547-7552.

[51] Wu, Q., Wang, S., Li, G., Liang, S., Lin, C.-J., Wang, Y., Cai, S., Liu, K., Hao, J., 2016. Temporal Trend and Spatial Distribution of

Speciated Atmospheric Mercury Emissions in China During 1978–2014. Environmental Science & Technology. 50,

13428-13435.

of

[52] Xiang, J., Liu, G., 2008. Distribution and sources of atmospheric mercury in urban areas of Wuhan, Resour. Environ. Eng. 22, 27-30.

-p

in a coastal city, Xiamen, China. Chemosphere. 119, 530-539.

ro

[53] Xu, L., Chen, J., Yang, L., Niu, Z., Tong, L., Yin, L., Chen, Y., 2015. Characteristics and sources of atmospheric mercury speciation

re

[54] Yang, Y., Chen, H., Wang, D., 2009. Spatial and temporal distribution of gaseous elemental mercury in Chongqing, China.

lP

Environmental monitoring and assessment. 156, 479.

[55] Yin, X., de Foy, B., Wu, K., Feng, C., Kang, S., Zhang, Q., 2019. Gaseous and particulate pollutants in Lhasa, Tibet during 2013–

na

2017: Spatial variability, temporal variations and implications. Environmental Pollution. 253, 68-77.

Jo ur

[56] Yin, X., Kang, S., Foy, B.d., Ma, Y., Tong, Y., Zhang, W., Wang, X., Zhang, G., Zhang, Q., 2018. Multi-year monitoring of

atmospheric total gaseous mercury at a remote high-altitude site (Nam Co, 4730 m asl) in the inland Tibetan Plateau region.

Atmospheric Chemistry and Physics. 18, 10557-10574.

[57] Yu, B., Wang, X., Lin, C.J., Fu, X., Zhang, H., Shang, L., Feng, X., 2015. Characteristics and potential sources of atmospheric

mercury at a subtropical near‐ coastal site in East China. Journal of Geophysical Research: Atmospheres. 120, 8563-8574.

[58] Zhang, H., Fu, X., Lin, C.-J., Wang, X., Feng, X., 2015. Observation and analysis of speciated atmospheric mercury in Shangri-La,

Tibetan Plateau, China. Atmospheric Chemistry & Physics. 15.

[59] Zhang, L., Wang, S., Wang, L., Hao, J., 2013. Atmospheric mercury concentration and chemical speciation at a rural site in Beijing,

China: implications of mercury emission sources. Atmospheric Chemistry and Physics. 13, 10505-10516.

20

Journal [60] Zhang, Y., Liu, R., Cui, Y., Zhou, J., Wang, Y., 2014. The Pre-proof characteristic analysis of atmospheric mercury during haze days in Qingdao, China Env. Sci. 34, 1905-1911.

[61] Zhao, S., Yu, Y., Qin, D., 2018. From highly polluted inland city of China to" Lanzhou Blue": The air-pollution characteristics.

Sciences in Cold and Arid Regions. 10, 12-26.

[62] Zhu, J., Wang, T., Talbot, R., Mao, H., Hall, C., Yang, X., Fu, C., Zhuang, B., Li, S., Han, Y., 2012. Characteristics of atmospheric

Jo ur

na

lP

re

-p

ro

of

total gaseous mercury (TGM) observed in urban Nanjing, China. Atmospheric Chemistry and Physics. 12, 12103-12118.

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Journal Pre-proofand manuscript is approved by all authors No conflict of interest exits in the submission of this manuscript, for publication. I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in

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whole or in part. All the authors listed have approved the manuscript that is enclosed.

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Xiufeng Yin: Conceptualization, Data curation, Writing - original draft. Wenting Zhou: Formal analysis, Visualization.

Journal Pre-proof

Shichang Kang: Conceptualization, Writing - review & editing. Benjamin de Foy: Writing - review & editing. Ye Yu: Methodology. Jin Xie: Visualization, Methodology. Shiwei Sun: Data curation. Kunpeng Wu: Software. Qianggong

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Zhang: Conceptualization, Data curation, Writing - review & editing.

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Pre-proof Latest observations of totalJournal gaseous mercury in a megacity (Lanzhou)

in northwest China Xiufeng Yin 1, 2, 3, Wenting Zhou 1, Shichang Kang 1, 3, 4, Benjamin de Foy 5, Ye Yu 6, Jin Xie 7, Shiwei Sun1, 3, Kunpeng Wu 8, Qianggong Zhang 2, 4 1

State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of

Science, Lanzhou, 730000, China 2

Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese

Academy of Sciences, Beijing, 100101, China 3

University of Chinese Academy of Sciences, Beijing, 100039, China

4

CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100085, China

5

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Department of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO, 63108, USA

6

Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute

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of Eco-Environment and Resources, Chinese Academy of Science, Lanzhou 730000, China 7

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China Meteorological Administration, National Meteorological Center, Beijing, 100081, China

8

to:

Qianggong

([email protected])

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na

([email protected])

Zhang

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Correspondence

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Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650091, China

24

and

Shichang

Kang

Journal Pre-proof Table 1. Atmospheric Hg concentrations at urban sites in China. Sites

TGM/GEM (ng m-3)

Type

Reference

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Shanghai Qiangdao Xiamen Ningbo Hefei Guangzhou Lanzhou Jiaxing Chongqing Nanjing Guiyang Beijing Wuhan Changchun

2.70; 4.19 2.80 3.50 3.79 4.07 4.60 4.62 5.40 6.74 7.90 8.40; 9.72; 10.20 10.40 14.80 18.40

Urban Urban Urban Urban Urban Urban Urban Urban Urban Urban Urban Urban Urban Urban

Friedli et al., 2011; Duan et al., 2017 Zhang et al., 2014. Xu et al., 2015. Nguyen et al., 2011. Hong et al., 2016 Chen et al., 2013. This study Wang et al., 2007. Yang et al., 2009. Zhu et al., 2012 Feng et al., 2004; Fu et al., 2015; Fu et al, 2011. Liu et al., 2002. Xiang et al., 2008. Fang et al., 2004.

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No.

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Table 2. Principle component analysis profiles of 5 factors contributing to TGM concentrations in Lanzhou based on factor loadings of 15 components along with eigenvalues and percentage of variance explained by each factor. Factor1 Factor 2 TGM SO2 CO NO2 PBLH SWD O3 RH T PM10 AQI PM2.5 WS O3_8h WD Q

0.44 0.84 0.83 0.83

-0.40

0.05

-0.22

0.46

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3.02 18.89

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Eigenvalues Variance explained (%)

0.44 0.56

0.96 0.91 0.80

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-0.40

Factor 5

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0.49

Factor 4

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0.87 0.85 0.74 -0.56 0.54

Factor 3

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0.74 0.64 -0.59 0.82

2.60 16.30

1.80 11.26

1.50 9.35

Pre-proof Latest observations of totalJournal gaseous mercury in a megacity (Lanzhou)

in northwest China Xiufeng Yin 1, 2, 3, Wenting Zhou 1, Shichang Kang 1, 3, 4, Benjamin de Foy 5, Ye Yu 6, Jin Xie 7, Shiwei Sun1, 3, Kunpeng Wu 8, Qianggong Zhang 2, 4 1

State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of

Science, Lanzhou, 730000, China 2

Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese

Academy of Sciences, Beijing, 100101, China 3

University of Chinese Academy of Sciences, Beijing, 100039, China

4

CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100085, China

5

of

Department of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO, 63108, USA

6

Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute

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of Eco-Environment and Resources, Chinese Academy of Science, Lanzhou 730000, China 7

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China Meteorological Administration, National Meteorological Center, Beijing, 100081, China

8

to:

Qianggong

([email protected])

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na

([email protected])

Zhang

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Correspondence

re

Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650091, China

27

and

Shichang

Kang

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Figure 1. Top: the geographical location of the city of Lanzhou, of the monitoring site, and of surrounding points of interest. Bottom right: view of the monitoring site which is located on the roof of the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences. Bottom left: view of the city looking west from the monitoring site.

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Figure 2. The geographical location of Lanzhou and sites with atmospheric mercury measurements in China, along with average measured concentrations from multiple studies. (Liu et al., 2016; Fu et al., 2012b; Fu et al., 2012a; Fu et al., 2015; Ci et al., 2011; Dou et al., 2013; Zhang et al., 2015; Friedile et al., 2011; Fu et al., 2010; Zhang et al., 2014; Li et al., 2011; Zhang et al., 2013; Yu et al., 2015; Xu et al., 2015; Nguyen et al., 2011; Hong et al., 2016; Fu et al., 2008; Duan et al., 2017; Chen et al., 2013; Wang et al., 2007; Yang et al., 2009; Zhu et al., 2012; Feng et al., 2004; Fu et al., 2015a; Fu et al., 2011; Liu et al., 2002; Xiang and Liu, 2008; Fang et al., 2004; Su et al., 2007; Wang et al., 1996)

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Figure 3. Monthly mean and statistical parameters of Total Gaseous Mercury (TGM) in Lanzhou during the whole measurement period (spring (MAM) in red; summer (JJA) in blue; autumn (SON) in dark red; and winter (DJF) in black).

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Figure 4. Variation of monthly mean Total Gaseous Mercury to carbon monoxide ratios (TGM/CO) in Lanzhou during the whole measurement period.

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Figure 5. Diurnal profiles of mean hourly total gaseous mercury in Lanzhou by seasons during the measurement period (mean and 95% confidence interval in mean).

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Figure 6. Polar plot of total gaseous mercury concentrations by wind speed and direction in Lanzhou during the whole measurement. Mean concentrations of TGM in certain wind speed and direction were displayed in different colors.

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Figure 7. Clusters of HYSPLIT backward trajectories (colored lines) based on hourly trajectories (gray lines) during the measurement period along with mean concentrations at the measurement site associated with each cluster (mean ± SD, bottom left), and average transport height of each cluster (bottom right).

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Figure 8. Concentrated Weighted Trajectory (CWT) analysis based on the HYSPLIT trajectories. Higher values indicate areas of air mass transport associated with higher total gaseous mercury concentrations in Lanzhou

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Figure 9. Total Gaseous Mercury (TGM) /Gaseous Elemental Mercury (GEM) concentrations in cities in China (Chongqing: Wang et al., 1996; Beijing: Liu et al., 2002; Changchun: Fang et al., 2004; Guiyang: Feng et al., 2004; Wuhan: Xiang and Liu, 2008; Lanzhou: Su et al., 2007; Jiaxing: Wang et al., 2007; Chongqing: Yang et al., 2009; Ningbo: Nguyen et al., 2011; Guiyang: Fu et al., 2011; Guiyang: Fu and Feng, 2015; Nanjing: Zhu et al., 2012; Xiamen: Xu et al., 2015; Qingdao: Zhang et al., 2014; Hefei: Hong et al., 2016; Shanghai: Duan et al., 2017; Lanzhou: this study).

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Pre-proof Latest observations of totalJournal gaseous mercury in a megacity (Lanzhou)

in northwest China Xiufeng Yin 1, 2, 3, Wenting Zhou 1, Shichang Kang 1, 3, 4, Benjamin de Foy 5, Ye Yu 6, Jin Xie 7, Shiwei Sun1, 3, Kunpeng Wu 8, Qianggong Zhang 2, 4 1

State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of

Science, Lanzhou, 730000, China 2

Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese

Academy of Sciences, Beijing, 100101, China 3

University of Chinese Academy of Sciences, Beijing, 100039, China

4

CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, 100085, China

5

of

Department of Earth and Atmospheric Sciences, Saint Louis University, St. Louis, MO, 63108, USA

6

Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute

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of Eco-Environment and Resources, Chinese Academy of Science, Lanzhou 730000, China 7

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China Meteorological Administration, National Meteorological Center, Beijing, 100081, China

8

to:

Qianggong

([email protected])

and

Shichang

Kang

na

([email protected])

Zhang

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Correspondence

re

Institute of International Rivers and Eco-Security, Yunnan University, Kunming, 650091, China

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1 Continuous TGM measurement in Lanzhou 2016-2017 showed an average of 4.48 ng m-3. 2 The sources of mercury were similar to other atmospheric pollutants (SO2, CO, NO2 and PM2.5), mainly from industrial combustion plants in urban districts.

3 Local-to-regional scale sources largely contributed to higher TGM concentrations. 4 Synthesis of atmospheric mercury measurements in China’s megacities revealed a general decrease in atmospheric mercury in the past few decades. 5 Implementation of atmospheric pollution emission control measures potentially lead to the decrease of atmospheric mercury concentrations in China’s megacities.

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Figure 1

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Figure 3

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Figure 6

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Figure 9