Meta-analysis of Heavy Metal and Arsenic Ecological-risk Assessment and Sources in Surface Sediments of Lake Wuliangsuhai, China

25 Heavy metal and arsenic (As) concentrations in the overlying water of Lake WLSH from 26 2013-2017 to evaluate the water quality of the lake. Heavy metal and As concentrations in Lake 27 WLSH surface sediment from studies performed between 2009-2017 were analyzed of heavy 28 metal geo-accumulation, potential ecological risk and toxicity data for Lake WLSH surface 29 sediment was performed to allow heavy metal and As pollution of Lake WLSH surface 30 sediment to be described clearly, objectively, and comprehensively. The following four main 31 conclusions were drawn. (1) The water quality index of the overlying water showed a tendency 32 of slight pollution in the lake from 2013 to 2017. (2) Pollution by the heavy metals (Cu, Zn, Pb, 33 Cd, Cr) and As in Lake WLSH should be given increased attention. (3) The geoaccumulation 34 indices showed that Cd is the most critical pollutant and that the probabilities of Lake WLSH 35 sediment being slightly polluted and moderately polluted were found to be 72.8% and 11.3%, 36 respectively. (4) Cd is the main contributor (75.2%) to potential ecological risks, and although 37 As is at a low toxicity level, its toxicity-risk contribution is higher than that of other metals 38 (approximately 31%). (5) Positive matrix factorization (PMF) model results indicated that 39 industrial and agricultural resources are the main suppliers of heavy metals to Lake WLSH 40 sediment, contributing 43.2% and 42.6% of the heavy metals and As. The summarized results 41 and conclusions can help the local government further understand heavy metals and As 42 pollution in Lake WLSH and develop corresponding pollution-control measures. This study 43 can also serve as a reference for future research on the heavy metals and As pollution of 44 sediment in Lake WLSH and other lakes.


Introduction 49
Lakes are indispensable wetlands for the global ecosystem and play important roles in 50 regulating river-water volume and improving the ecological environment (Liu et al., 2020). In 51 recent years, with the changes in regional climate and environment and the aggravation of 52 human activities, lake-ecosystem degradation, water eutrophication, and water pollution have 53 become major global problems (Yang et al. 2008; Nazari-Sharabian et al. 2018; Benateau et al. 54 2019). In developing countries such as China, the rapid industrial and agricultural growth, as 55 well as other human activities, have led to rising levels of heavy metals in river and lake 56 sediments ; Yan et al. 2018). Accordingly, heavy-metal and As pollution in 57 aquatic environment has become a research hotspot because of its toxicity, persistence, and 58 bioaccumulation to the environment, as well as its adverse effects on organisms and the entire 59 ecosystem (Lin et al. 2016). Lake sediment, as an important part of water ecosystem, provide 60 habitats and food sources for benthic organisms and also serve as secondary sources and 61 reservoirs of heavy metals in water (Yi et al. 2011). To protect the ecological security of lakes, 62 it is important to study the content of heavy metals and As in lake sediments and the associated 63 of Lake WLSH were collected to assess heavy-metal and As pollution levels and potential 122 ecological risks. The main objectives of this work were as follows: (1) determine the spatial 123 distribution of heavy metals and As in the surface sediments of Lake WLSH by collecting data 124 from published papers; (2) use the Igeo, potential ecological RI assessment, and TU to assess the 125 pollution levels and potential ecological risks of heavy metals and As in the surface sediments rating and the grading standards, the overall nutrient level in Lake WLSH is mid-eutrophic 140 , and the annual average deposition depth was 9.61 mm (Yu et al. 2012). The 141 inlet and outflow channels around Lake WLSH are shown in Fig. S1 (Supplementary materials). 142 Since 2000, industries around Lake WLSH (paper mill, pharmaceutical factory, and smelter, 143 etc.) have developed rapidly in an attempt to develop the local economy, and the lake, which 144 receives industrial, agricultural, and residential wastewater, has gradually been polluted (Zhang 147 Data collection 148 The following databases were used to retrieve published literature: ISI Web of Science for 149 searching English literature, China National Knowledge Infrastructure, and Wan Fang Data for 150 searching Chinese literature (Fig. 1a). The search terms " 'Wuliangsuhai' or 'Ulansuhai' " and 151 "metal" were used in the databases, covering studies from 2000 to 2019. To ensure data integrity 152 and continuity, 12 of 172 papers were selected to obtain the data of heavy metals in sediment 153 from 2009 to 2017. In this paper, Lake WLSH was divided into entrance, central, and exit zones 154 based on lake hydraulics and inlet channel flows in the selected literature, as described in 155 Supplementary Materials. The criteria for selecting published literature in this research were as 156 follows: (i) the publications that were selected for this research should involve the investigation 157 of the surface sediments (5-20 cm) in the entire Lake WLSH (i.e., the entrance, central, and exit 158 zones), as shown in Fig. 1b; (ii) the selected literature included sampling information (i.e., 159 sampling date, number of samples, sampling site location, and measured heavy-metal and As 160 concentration), and (iii) the heavy-metal and As concentrations were determined using the same 161 or similar standards. 162  Tab.1. Based on the water-quality index (WQI), the comprehensive pollution-index  172   method takes the heavy metals observed at the same measuring point as a whole to study their  173 influence on the environment under the condition of interaction (Bewers 1995;Cheng et al. 174 2002). Equations are as follows: 175 Pi, represents the pollution index of i th heavy metal and As. Ci represents the measured 178 concentration of the i th heavy metal and As (μg L -1 ). Si, represents the evaluation standard of 179 heavy metal and As (μg L -1 ). Surface water environmental quality standards was used Chinese 180 GB3838-2002, in which the standard limits of Cu, Zn, Pb, Cd, Cr and As are 1000, 1000, 50, 181 5, 50 and 50 μg L -1 , respectively. n is the number of heavy metals and As. WQI consists of three 182 grades as follows (Bewers 1995 However, this is currently still a relatively general screening method that can provide a guide 189 for lake sediment pollution management (Allen Burton 2018). The level of enrichment and 190 toxicity risk of heavy metals and As in the sediments of Lake WLSH were evaluated using the 191 Igeo, potential ecological RI, and TU. The evaluation methods of Igeo, RI, and TU were as follows. 192 Igeo is primarily used to assess the degree of heavy-metal and As pollution by deducting 193 sediment or soil background content from the measured heavy-metal and As content. The Igeo where Cn is the concentration of the n th heavy metal and As measured in sediment. Bn is 197 the background value of the n th heavy metal and As. The correction coefficient of factors such 198 as sedimentary characteristics is 1.5. Igeo consists of five grades (Muller 1969), as shown in Tab. 199

200
The method developed by Hakanson was used to calculate the potential ecological RI 201 caused by the total pollution of the Lake WLSH (Hakanson 1980), as shown in Tab. 2. 202 RI is the potential ecological 205 risks. C i s is the measured concentration of the i th heavy metal and As in sediment (mg kg -1 ). C i n 206 is the background values of the i th heavy metal and As (mg kg -1 ). T i r is the toxic response factor 207 for a given heavy metal and As, i.e., 5, 5, 5, 30, 10 and 5 for Cu, Zn, Pb, Cd, Cr and As 208 respectively. 209 TU evaluation method can be used to determine the influence of heavy metals and As in 210 sediments on water environment (Pedersen et al. 1998 Paatero first proposed the PMF model in 1994, and the method was approved by the U S 223 Environmental Protection Agency for identifying air pollution sources (Paatero 1997). The 224 greatest advantage of the PMF model is that no source profiles are required, and uncertainty is 225 used to weight all the data (Niu et al. 2020). Potential sources of heavy metals and As in WLSH 226 Lake sediments were identified using the PMF 5.0 model, and pollution sources were analyzed 227 using the distribution of five heavy metals and As in Lake WLSH. The aim of the PMF model 228 is to use the concentration and source profiles of the species of interest to solve the mass balance 229 of the species of interest, the calculation equations are as follows (Norris et al. 2014). 230 1 ( 1, 2,3 n; 1, 2,3 m) xik is the heavy metal concentration; gi is factor to sample contribution; fkj is profile species 232 of each source; i, j are the number of samples and chemical species, respectively, and eij 233 represents the sample. 234 Factor contributions and profiles are derived by the PMF model minimizing the objective 235 function Q, and Q is a critical parameter for PMF (Norris et al. 2014). 236 In this study, the concentration of each sample was above the detection limit and the 238 uncertainty value was calculated according to the following equation (Norris et al. 2014).
Concentrations below the method detection limit (MDL) were calculated using Eq. (9), while 240 otherwise Eq. (10) was used. 241 Where, Unc is uncertainty of the concentration; MDL is the method detection limit (Norris 244 et al. 2014). 245 246

Results and discussion 247
Selected studies 248 Tab. 3 showed a summary of heavy-metal and As concentrations in the surface sediments 249 based on the 12 papers selected. Cu, Zn, Pb, Cd, Cr, and As in the surface sediment of Lake 250 WLSH deserved special attention. In the lake surface sediments, Cd and As were relatively 251 high, which were 6 and 4.7 times of the background values, respectively, and Cu was 2.3 times 252 of the background value. Zn, Pb, and Cr were relatively low, ranging from 1.1 to 1.5 times of 253 the background values and slightly higher than the values. From the perspective of coefficient 254 of variation, Cd was at 82%, Pb and As were at 45%, and other heavy metals were at 33%-255 39%. These results showed that Cd concentrations greatly varied in space, and the Cd contents 256 in the sediments of Lake WLSH was highly uncertainty. Compared with the average 257 concentrations of heavy metals and As in surface sediments of Lake Taihu (Niu et al. 2020), 258 Cu, Zn, Cd and Cr in Lake WLSH were similar to those in Taihu Lake, but the average 259 concentration of Pb in Lake Taihu was 1.83 times higher than that in Lake WLSH, while the 260 average concentration of As in Lake WLSH was 3.72 times higher than that in Lake Taihu. Pb 261 in lake sediments mainly originates from human activities such as industry and transportation 262 (Yao et al. 2008). Compared with Lake Taihu, Lake WLSH has weaker human activities, which leads to higher Pb concentration in surface sediments of Lake Taihu than Lake WLSH. 264 Compared with Lake Taihu, industry and agriculture around WLSH Lake basically account for 265 90% of the economy (Inner Mongolia Autonomous Region Bureau of Statistics 2020). 266 Industrial wastewater (paper mills, pharmaceutical manufacturers and metal smelters) and 267 agricultural wastewater (pesticides, fertilizers) are discharged into Lake WLSH through ditches 268 (Zhang 2010; Lv 2018; Lou et al. 2020), which results in As concentrations in this lake being 269 3.72 times higher than those in Lake Taihu. 270 Table 3  Tab.1 shows that the concentrations of Cd and As in the overlying water belong to Class I 283 standard, Cu, Zn, and Cr to Class II standard, and Pb to Class III standard. Therefore, the 284 overlying water standard of WLSH Lake was determined to be Class III according to the 285 environmental quality standard for surface water (GB3838-2002 of China). The WQI method 286 can be used to deal with heavy metals observed at the same measurement location as a whole 287 and examine the impact of these heavy metals and As on the environment through interactions (Cheng et al. 2002). Fig. 3 shows that the WQI of the lake entrance, center, and exit zones were 289 all less than 1, and were in a no polluted status from 2013 to 2017. However, the WQI of 2017 290 was about twice as high as in previous years, the overlying water of Lake WLSH showed a 291 tendency of slight pollution, and the pollution of the lake exit zone increased significantly 292 compared with other zones. These results indicated that the overlying water of Lake WLSH 293 will be polluted by heavy metals and As if no corresponding treatment measures are taken. 294  To better reflect the heavy-metal and As pollution in the surface sediments of Lake WLSH, 315 Igeo, RI, and TU were used to evaluate the reported element-concentration distribution 316 characteristics. Igeo was calculated for the entrance, center, and exit zones of Lake WLSH using 317 Eq. 3 (Muller 1969). The Igeo values for each zone of the lake are shown in Fig. 5. The highest 318 Igeo values for Cd and As in the sediments of the Lake WLSH indicated moderate pollution, and 319 those for Cd indicated more moderate pollution and heavy pollution in the lake exit zone.

E i
r and E i r /RI indices were calculated for the entry, center, and exit zones of the Lake WLSH 338 by using Eqs. 2 and 3 (Hakanson 1980), as shown in Fig. 6. The E i r values of Cd in the three 339 zones of the lake were greater than 160, indicating high risk; and those of the remaining heavy 340 metals and As were less than 40, indicating low risk (Fig. 6a). The high Cd Igeo values also 341 caused high RIs. Cd contributed 75.2% of the potential ecological risk (Fig. 6b), and Cd 342 potential ecological risk in the exit zone is slightly higher than in the other two zones. Cd was 343 also the main contributor to the potential ecological risk in the sediments of Lake Taihu . In this paper, comparing the heavy metals and As concentrations in Lake WLSH than ERM, the maximum concentrations of Cu and Cd were lower than ERL, and the maximum 363 concentrations of Zn, Pb, and Cr were distributed between ERL and ERM. Compared with TEL 364 and PEL, the maximum concentrations of Pb, Cr and As were higher than the PEL and the 365 maximum concentrations of Cu, Zn and Cd were between the TEL and the PEL. In this paper, 366 comparing the heavy metals and As concentrations in Lake WLSH sediments with ERL and 367 ERM, the maximum concentrations of As were found to be higher than ERM, the maximum 368 concentrations of Cu and Cd were lower than ERL, and the maximum concentrations of Zn, Pb, 369 and Cr were distributed between ERL and ERM. Compared with TEL and PEL, the maximum 370 concentrations of Pb, Cr and As were higher than the PEL and the maximum concentrations of 371 Cu, Zn and Cd were between the TEL and the PEL. Toxicity characteristics of heavy metals 372 and As in the sediments of Lake WLSH were calculated by Eq. 6 (Pedersen et al. 1998). The 373 statistical results are shown in Fig. 7. The risk profile of the sediment TU's and ΣTU's in the 374 lake showed that the ΣTU's in the entrance, center, and exit zones were 2.96, 2.78, and 2.75, 375 respectively, indicating low toxicity level, but the lake entrance zone was more polluted. And 376 As of TU's were all higher than heavy metals (Cu, Zn, Pb, Cd, and Cr) in the three zones of the 377 lake, were 0.99, 0.89, and 0.75, respectively, indicating low toxicity level. The TU's of the 378 heavy metals and As were also less than 4, indicating low toxicity grade (Fig. 7a). As metal 379 contributed 33.44%, 32.29%, and 27.26% of TU's in the entrance, center, and exit zones of the 380 lake, respectively (Fig. 7b). The toxicity of heavy metals and As in the sediments of Lake 381 WLSH was As, with a total toxicity contribution of about 30.98%; while the toxicity of heavy 382 metals in the sediments of Lake Taihu was Pb, with a total toxicity contribution of about 32% 383 (Niu et al. 2020). Arsenic in sediments is generally present mainly in the low solubility form, 384 bound primarily to iron oxides and present in the residual phase, and will be released into the 385 overlying water as the sediment conditions (e.g., temperature, pH, etc.) change (Nikolaidis et al. 2004;Arain et al. 2009). Therefore, the sources of pollution in Lake WLSH need to be 387 effectively identified and appropriate control measures should be developed. 388 Factor 2 explains only 4.2% of the contribution of different sources of heavy metals and 410 arsenic to heavy metal and arsenic concentrations in the sediment of Lake WLSH, and factor 411 loadings are low (<10%) for all heavy metals and 0 for As. In geochemical baseline studies, natural sources of heavy metals and As contribute to background values of concentrations in 413 local soils and sediments. Anthropogenic sources contributed much more heavy metals and As 414 to lake sediments than natural sources (Niu et al. 2020), and non-anthropogenic sources 415 contributed slightly to heavy metal and As concentrations in the sediment of Lake WLSH. 416 Hence, factor 2 is related to natural sources. Zn, Pb, Cd, and Cr) and As were the most concern in the surface sediment of the lake between 445 2009 and 2017. In terms of cumulative contamination and potential ecological risk, the lake 446 sediment was most heavily contaminated with Cd, accounting for 75.2% of the potential 447 ecological risk (assessed using RI). Within a toxicity-risk control perspective, although As is at 448 a low toxicity level, its toxicity-risk contribution is higher than that of other metals 449 (approximately 31%). The PMF model indicated that heavy metals and As in Lake WLSH 450 sediment have mainly been supplied by industrial and agricultural resources, which have 451 contributed 43.2% and 42.6% of the total heavy metal and As concentrations, respectively. 452 Natural sources and atmospheric deposition sources have contributed 4.2% and 10.0%, 453 respectively, of the total heavy metal and As concentrations. In order to prevent heavy metals 454 and As in drainage ditch sediment being transported into Lake WLSH because of human 455 activities such as lake ecological water replenishment, the wastewater discharges from 456 industrial and agricultural sources also need to be controlled and monitored more effectively 457 than is currently the case. All these results can provide comprehensive and quantitative 458 reference data for heavy metal and As pollution in Lake WLSH. 459   Table. 1 Statistical description of heavy-metal and As guideline values for overlying water 699

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and water quality grade. 700

Category
Overlying water heavy-metal and As concentrations (μg L -1 )