土壤污染生态阈值研究进展
Advances in Ecological Thresholds of Soil Contaminants
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摘要: 目前我国现行的土壤环境质量标准主要以人体健康风险和食物链风险为主，对生态安全关注较少，缺乏生态风险的相关内容。准确推导土壤污染生态阈值，是制定土壤环境质量基准及标准的重要基础。本文围绕当前国内外常用土壤污染生态阈值推导过程，以及基于植物和土壤无脊椎动物个体以及微生物群落等不同生态受体推导生态阈值的优缺点进行了综述。针对目前推导土壤污染生态阈值的主要程序，即：基于实验室内生态毒性数据进行统计外推的方法存在物种代表性不足、生态相关性差以及缺乏场地-特异性等缺点，指出基于野外调查数据，利用机器学习算法构建精确度高、准确性强的污染物暴露剂量-效应模型的可行性，提出整合文献和毒理数据库中个体水平及野外生物群落水平生态毒性效应数据的场地-特异性土壤污染生态阈值推导框架；同时建议今后重点开展以下4个方面的工作：（1）野外土壤生物群落评估终点指标体系建立；（2）场地-特异性暴露-效应关系模型构建；（3）实验室生态毒理数据的筛查、评价及野外校正；（4）土壤生物毒理数据库平台搭建。以期为科学合理地制定基于生态风险土壤环境质量基准及标准提供重要的理论基础和技术支撑。Abstract: Currently, soil environmental quality standards in China have been established primarily focusing on human health and food chain risks, while paying less attention to ecological security, and lacking perspectives of ecological risks. Accurately derived ecological thresholds of soil pollutants is the key for formulating soil environmental quality benchmarks and standards. In this paper, we reviewed the derivation processes of ecological thresholds for soil pollutants commonly used domestically and internationally. Advantages and disadvantages of ecological thresholds derived based on different ecological receptors such as plants, soil invertebrates and microbial communities were also discussed. Disadvantages of currently ecological thresholds which are derived based on the ecological toxicity data of plants and soil invertebrates in laboratories coupled with statistical extrapolation methods include insufficient species representation, poor ecological relevance and a lack of site-specificity. It was suggested that machine learning algorithms based on field survey data of contaminated sites could be used as a feasible way to construct exposure-effect models with high precision and accuracy. A site-specific ecological threshold deriving framework base on integrating ecotoxicity data at individual level from literature and toxicity database and ecotoxicity data at community level in fields was proposed. Future studies were suggested as follows:(1) establishment of metrics systems for effect endpoints at community level in field; (2) construction of site-specific exposure-effect models; (3) screening and field evaluation and field calibration of ecotoxicity data at individual level from lab experiments; (4) establishment of soil biological toxicology database platform. The aim of this review was to provide an important theoretical basis and technical support for the scientific and rational development of soil environmental quality criteria and standards based on ecological risks.
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Hu B F, Shao S, Ni H, et al. Current status, spatial features, health risks, and potential driving factors of soil heavy metal pollution in China at province level [J]. Environmental Pollution, 2020, 266(Pt 3):114961 Zhang H W, Zhang F, Song J, et al. Pollutant source, ecological and human health risks assessment of heavy metals in soils from coal mining areas in Xinjiang, China [J]. Environmental Research, 2021, 202:111702 环境保护部, 国土资源部. 全国土壤污染状况调查公报[R]. 北京:环境保护部, 国土资源部, 2014 生态环境部, 国家市场监督管理总局. 土壤环境质量农用地土壤污染风险管控标准:GB 15618-2018[S]. 北京:中国标准出版社, 2018 生态环境部, 国家市场监督管理总局. 土壤环境质量建设用地土壤污染风险管控标准:GB 36600-2018[S]. 北京:中国标准出版社, 2018 冯艳红, 张亚, 林玉锁, 等. 基于生态风险的土壤环境基准研究概况[C]//中国环境科学学会. 2016中国环境科学学会学术年会论文集(第三卷). 海口:中国环境科学学会, 2016:1110-1113 李勖之, 姜瑢, 孙丽, 等. 不同国家土壤生态筛选值比较与启示[J]. 环境化学, 2022, 41(3):1001-1010 Li X Z, Jiang R, Sun L, et al. Ecological soil screening values among different countries and implication for China [J]. Environmental Chemistry, 2022, 41(3):1001-1010(in Chinese)
郑丽萍, 王国庆, 李勖之, 等. 基于保护生态的土壤基准值制订关键技术研究:以美国和澳大利亚为例[J]. 生态毒理学报, 2021, 16(1):165-176 Zheng L P, Wang G Q, Li X Z, et al. Research on key techniques for the formulation of soil environmental benchmarks based on ecologically protection:The case of the United States and Australia [J]. Asian Journal of Ecotoxicology, 2021, 16(1):165-176(in Chinese)
曾庆楠, 安毅, 秦莉, 等. 物种敏感性分布法在建立土壤生态阈值方面的研究进展[J]. 安全与环境学报, 2018, 18(3):1220-1224 Zeng Q N, An Y, Qin L, et al. Advances on species sensitivity distribution in deriving soil ecological thresholds [J]. Journal of Safety and Environment, 2018, 18(3):1220-1224(in Chinese)
Reimann C, Fabian K, Birke M, et al. GEMAS:Establishing geochemical background and threshold for 53 chemical elements in European agricultural soil [J]. Applied Geochemistry, 2018, 88:302-318 Du Z L, Lin D S, Li H F, et al. Bibliometric analysis of the influencing factors, derivation, and application of heavy metal thresholds in soil [J]. International Journal of Environmental Research and Public Health, 2022, 19(11):6561 王美娥, 丁寿康, 郭观林, 等. 污染场地土壤生态风险评估研究进展[J]. 应用生态学报, 2020, 31(11):3946-3958 Wang M E, Ding S K, Guo G L, et al. Advances in ecological risk assessment of soil in contaminated sites [J]. Chinese Journal of Applied Ecology, 2020, 31(11):3946-3958(in Chinese)
United States Environmental Protection Agency (US EPA). Guidance for developing ecological soil screening levels [R]. Washington DC:United States Environmental Protection Agency, 2005 Canadian Council of Ministers of the Environment (CCME). A protocol for the derivation of environmental and human health soil quality guidelines [R]. Ottawa:Canadian Council of Ministers of the Environment, 2006 Environment Agency (EA). Derivation and use of soil screening values for assessing ecological risk (Science Report share id26) [R]. Bristol:Environment Agency, 2017 Swartjes F A, Rutgers M, Lijzen J P A, et al. State of the art of contaminated site management in The Netherlands:Policy framework and risk assessment tools [J]. Science of the Total Environment, 2012, 427-428:1-10 National Environment Protection Council (NEPC). Schedule B(5), guideline on ecological risk assessment, national environment protection (assessment of site contamination) measure 1999[R]. Adelaide:NEPC, 2013 National Environment Protection Council (NEPC). Schedule B(1), guideline on the investigation levels for soil and groundwater, national environment protection (assessment of site contamination) measure 2013[R]. Adelaide:NEPC, 2013 National Environment Protection Council (NEPC). Schedule B5b, guideline on methodology to derive ecological investigation levels in contaminated soils [R]. Adelaide:NEPC, 2013 王小庆. 中国农业土壤中铜和镍的生态阈值研究[D]. 北京:中国矿业大学(北京), 2012:51-88 Wang X Q. Ecological thresholds for copper and nickel in Chinese agricultural soils [D]. Beijing:China University of Mining & Technology, Beijing, 2012:51-88(in Chinese) 李宁. 基于不同终点测定土壤铅的生态风险阈值及其预测模型[D]. 北京:中国农业科学院, 2016:30-32 Li N. The toxicity thresholds (ECx) of Pb and its predicted models based on various endpoint determination [D]. Beijing:Chinese Academy of Agricultural Sciences, 2016:30 -32(in Chinese)
蒋宝. 土壤铜镍长期老化行为及有效态生态阈值研究[D]. 北京:中国农业大学, 2017:89-92 Jiang B. Long-term aging behavior of soil added nickel and copper and ecological thresholds based on extractable copper in soils [D]. Beijing:China Agricultural University, 2017:89 -92(in Chinese)
万亚男. 我国土壤中锌的生态阈值研究[D]. 北京:中国农业科学院, 2020:18-35 Wan Y N. Ecological thresholds for zinc in Chinese soils [D]. Beijing:Chinese Academy of Agricultural Sciences, 2020:18 -35(in Chinese)
李勖之, 郑丽萍, 张亚, 等. 应用物种敏感分布法建立铅的生态安全土壤环境基准研究[J]. 生态毒理学报, 2021, 16(1):107-118 Li X Z, Zheng L P, Zhang Y, et al. Derivation of ecological safety based soil quality criteria for lead by species sensitivity distribution [J]. Asian Journal of Ecotoxicology, 2021, 16(1):107-118(in Chinese)
李勖之, 孙丽, 杜俊洋, 等. 农用地土壤重金属锌的生态安全阈值研究[J]. 环境科学学报, 2022, 42(7):408-420 Li X Z, Sun L, Du J Y, et al. Soil ecological safety thresholds for zinc in agricultural land [J]. Acta Scientiae Circumstantiae, 2022, 42(7):408-420(in Chinese)
Zhao S W, Qin L Y, Wang L F, et al. Ecological risk thresholds for Zn in Chinese soils [J]. The Science of the Total Environment, 2022, 833:155182 Qin L Y, Sun X Y, Yu L, et al. Ecological risk threshold for Pb in Chinese soils [J]. Journal of Hazardous Materials, 2023, 444(Pt A):130418 Schwarz C. Improving statistical methods for modeling species sensitivity distributions [R]. Province of British Columbia, Victoria:BC Ministry of Environment and Climate Change Strategy, 2019 Fox D R, van Dam R A, Fisher R, et al. Recent developments in species sensitivity distribution modeling [J]. Environmental Toxicology and Chemistry, 2021, 40(2):293-308 黄兴华, 李勖之, 王国庆, 等. 保护陆生生态的土壤铜环境基准研究[J]. 中国环境科学, 2022, 42(10):4720-4730 Huang X H, Li X Z, Wang G Q, et al. Study of soil environmental criteria of copper for protection of terrestrial ecosystem [J]. China Environmental Science, 2022, 42(10):4720-4730(in Chinese)
江建平, 杜诚, 刘冰, 等. 中国生物物种编目进展与展望[J]. 生物多样性, 2022, 30(10):106-120 Jiang J P, Du C, Liu B, et al. Bio-inventory in China:Progress and perspectives [J]. Biodiversity Science, 2022, 30(10):106-120(in Chinese)
罗晶晶, 吴凡, 张加文, 等. 我国土壤受试植物筛选与毒性预测[J]. 中国环境科学, 2022, 42(7):3295-3305 Luo J J, Wu F, Zhang J W, et al. Screening of soil test plants and developing of their toxicity prediction models in China [J]. China Environmental Science, 2022, 42(7):3295-3305(in Chinese)
Bejarano A C, Barron M G. Aqueous and tissue residue-based interspecies correlation estimation models provide conservative hazard estimates for aromatic compounds [J]. Environmental Toxicology and Chemistry, 2016, 35(1):56-64 Willming M M, Lilavois C R, Barron M G, et al. Acute toxicity prediction to threatened and endangered species using interspecies correlation estimation (ICE) models [J]. Environmental Science & Technology, 2016, 50(19):10700-10707 Fan J T, Yan Z G, Zheng X, et al. Development of interspecies correlation estimation (ICE) models to predict the reproduction toxicity of EDCs to aquatic species [J]. Chemosphere, 2019, 224:833-839 Wang X N, Fan B, Fan M, et al. Development and use of interspecies correlation estimation models in China for potential application in water quality criteria [J]. Chemosphere, 2020, 240:124848 Barron M G, Lambert F N. Potential for interspecies toxicity estimation in soil invertebrates [J]. Toxics, 2021, 9(10):265 陈保冬, 赵方杰, 张莘, 等. 土壤生物与土壤污染研究前沿与展望[J]. 生态学报, 2015, 35(20):6604-6613 Chen B D, Zhao F J, Zhang X, et al. Soil pollution and soil organisms:An overview of research progress and perspectives [J]. Acta Ecologica Sinica, 2015, 35(20):6604-6613(in Chinese)
Liu Y Q, Du Q Y, Wang Q, et al. Causal inference between bioavailability of heavy metals and environmental factors in a large-scale region [J]. Environmental Pollution, 2017, 226:370-378 李波. 外源重金属铜、镍的植物毒害及预测模型研究[D]. 北京:中国农业科学院, 2010:24-58 Li B. The phytotoxicity of added copper and nickel to soils and predictive models [D]. Beijing:Chinese Academy of Agricultural Sciences, 2010:24 -58(in Chinese)
黄锦孙. 土壤铜镍植物毒害的室内和田间实验差异研究[D]. 北京:中国农业科学院, 2012:27-44 Huang J S. Differences between laboratory and field tests for phytotoxicity of copper and nickel in soils [D]. Beijing:Chinese Academy of Agricultural Sciences, 2012:27 -44(in Chinese)
Qin L Y, Wang M, Zhao S W, et al. Effect of soil leaching on the toxicity thresholds (ECx) of Zn in soils with different properties [J]. Ecotoxicology and Environmental Safety, 2021, 228:112999 Jänsch S, Römbke J, Schallnass H J, et al. Derivation of soil values for the path ‘soil-soil organisms’ for metals and selected organic compounds using species sensitivity distributions [J]. Environmental Science and Pollution Research International, 2007, 14(5):308-318 Smolders E, Oorts K, Van Sprang P, et al. Toxicity of trace metals in soil as affected by soil type and aging after contamination:Using calibrated bioavailability models to set ecological soil standards [J]. Environmental Toxicology and Chemistry, 2009, 28(8):1633-1642 Swartjes F A. Dealing with Contaminated Sites [M]. Dordrecht, the Netherlands:Springer Science & Business Media, 2011:579-582 Faber J H, van Wensem J. Elaborations on the use of the ecosystem services concept for application in ecological risk assessment for soils [J]. Science of the Total Environment, 2012, 415:3-8 Sokol N W, Slessarev E, Marschmann G L, et al. Life and death in the soil microbiome:How ecological processes influence biogeochemistry [J]. Nature Reviews Microbiology, 2022, 20(7):415-430 United States Environmental Protection Agency (US EPA). Attachment 1-2 guidance for developing ecological soil screening levels (Eco-SSLs) [R]. Washington DC:United States Environmental Protection Agency, 2003 Karpouzas D G, Kandeler E, Bru D, et al. A tiered assessment approach based on standardized methods to estimate the impact of nicosulfuron on the abundance and function of the soil microbial community [J]. Soil Biology and Biochemistry, 2014, 75:282-291 Karas P A, Baguelin C, Pertile G, et al. Assessment of the impact of three pesticides on microbial dynamics and functions in a lab-to-field experimental approach [J]. The Science of the Total Environment, 2018, 637-638:636-646 张倩倩, 乔敏, 池海峰. 土壤生态毒性测试方法综述[J]. 生态毒理学报, 2017, 12(4):76-97 Zhang Q Q, Qiao M, Chi H F. Overview of soil ecotoxicity tests [J]. Asian Journal of Ecotoxicology, 2017, 12(4):76-97(in Chinese)
Renella G, Ortigoza A L R, Landi L, et al. Additive effects of copper and zinc on cadmium toxicity on phosphatase activities and ATP content of soil as estimated by the ecological dose (ED50) [J]. Soil Biology and Biochemistry, 2003, 35(9):1203-1210 Cheng J J, Song J, Ding C F, et al. Ecotoxicity of benzo[a]pyrene assessed by soil microbial indicators [J]. Environmental Toxicology and Chemistry, 2014, 33(9):1930-1936 Epelde L, Muñiz O, Garbisu C. Microbial properties for the derivation of critical risk limits in cadmium contaminated soil [J]. Applied Soil Ecology, 2016, 99:19-28 Ghiglione J F, Martin-Laurent F, Pesce S. Microbial ecotoxicology:An emerging discipline facing contemporary environmental threats [J]. Environmental Science and Pollution Research International, 2016, 23(5):3981-3983 Andreoni V, Cavalca L, Rao M A, et al. Bacterial communities and enzyme activities of PAHs polluted soils [J]. Chemosphere, 2004, 57(5):401-412 张瀚丹, 刘新会, 王宇静, 等. 土壤剖面重金属污染对微生物群落结构的影响[J]. 环境科学与技术, 2022, 45(4):184-191 Zhang H D, Liu X H, Wang Y J, et al. Effects of heavy metal pollution on microbial community in soil profiles [J]. Environmental Science & Technology, 2022, 45(4):184-191(in Chinese)
Cui Y X, Wang X, Wang X X, et al. Evaluation methods of heavy metal pollution in soils based on enzyme activities:A review [J]. Soil Ecology Letters, 2021, 3(3):169-177 Brandt K K, Amézquita A, Backhaus T, et al. Ecotoxicological assessment of antibiotics:A call for improved consideration of microorganisms [J]. Environment International, 2015, 85:189-205 Storck V, Nikolaki S, Perruchon C, et al. Lab to field assessment of the ecotoxicological impact of chlorpyrifos, isoproturon, or tebuconazole on the diversity and composition of the soil bacterial community [J]. Frontiers in Microbiology, 2018, 9:1412 Jiang B, Adebayo A, Jia J L, et al. Impacts of heavy metals and soil properties at a Nigerian e-waste site on soil microbial community [J]. Journal of Hazardous Materials, 2019, 362:187-195 Lahlali R, Ibrahim D S S, Belabess Z, et al. High-throughput molecular technologies for unraveling the mystery of soil microbial community:Challenges and future prospects [J]. Heliyon, 2021, 7(10):e08142 Martiny J B H, Jones S E, Lennon J T, et al. Microbiomes in light of traits:A phylogenetic perspective [J]. Science, 2015, 350(6261):aac9323 Cébron A, Zeghal E, Usseglio-Polatera P, et al. BactoTraits:A functional trait database to evaluate how natural and man-induced changes influence the assembly of bacterial communities [J]. Ecological Indicators, 2021, 130:108047 Iordache V, Neagoe A. Conceptual methodological framework for the resilience of biogeochemical services to heavy metals stress [J]. Journal of Environmental Management, 2023, 325(Pt B):116401 Jiang R, Wang M E, Chen W P, et al. Ecological risk of combined pollution on soil ecosystem functions:Insight from the functional sensitivity and stability [J]. Environmental Pollution, 2019, 255(Pt 1):113184 Wang Z Q, Tian H X, Tan X P, et al. Long-term As contamination alters soil enzyme functional stability in response to additional heat disturbance [J]. Chemosphere, 2019, 229:471-480 Lessard I, Sauvé S, Deschênes L. Enzymatic functional stability of Zn-contaminated field-collected soils:An ecotoxicological perspective [J]. Science of the Total Environment, 2014, 484:1-9 Delgado-Baquerizo M, Maestre F T, Reich P B, et al. Microbial diversity drives multifunctionality in terrestrial ecosystems [J]. Nature Communications, 2016, 7:10541 Pu Q, Zhang K, Poulain A J, et al. Mercury drives microbial community assembly and ecosystem multifunctionality across a Hg contamination gradient in rice paddies [J]. Journal of Hazardous Materials, 2022, 435:129055 Jiang R, Wang M E, Xie T, et al. Site-specific ecological effect assessment at community level for polymetallic contaminated soil [J]. Journal of Hazardous Materials, 2023, 445:130531 Cormier S M, Suter G W 2nd. A method for deriving water-quality benchmarks using field data [J]. Environmental Toxicology and Chemistry, 2013, 32(2):255-262 Hoondert R P J, Hilbers J P, Hendriks A J, et al. Deriving field-based ecological risks for bird species [J]. Environmental Science & Technology, 2018, 52(6):3716-3726 Canadian Council of Ministers of the Environment (CCME). Ecological risk assessment guidance document [R]. Winnipeg:Canadian Council of Ministers of the Environment, 2020 Zhang J, Yu F B, Hu X G, et al. Multifeature superposition analysis of the effects of microplastics on microbial communities in realistic environments [J]. Environment International, 2022, 162:107172 Zhang Y, Lei M, Li K, et al. Spatial prediction of soil contamination based on machine learning:A review [J]. Frontiers of Environmental Science & Engineering, 2023, 17(8):93 Sakizadeh M, Mirzaei R, Ghorbani H. Support vector machine and artificial neural network to model soil pollution:A case study in Semnan Province, Iran [J]. Neural Computing and Applications, 2017, 28(11):3229-3238 范俊楠, 张钰, 贺小敏, 等. 基于BP神经网络的重点行业企业周边土壤重金属污染预测及评价[J]. 华中农业大学学报, 2019, 38(4):55-62 Fan J N, Zhang Y, He X M, et al. BP neural network based prediction and evaluation of heavy metal pollution in soil around the enterprises in key areas of Hubei Province [J]. Journal of Huazhong Agricultural University, 2019, 38(4):55-62(in Chinese)
Liu G, Zhou X, Li Q, et al. Spatial distribution prediction of soil As in a large-scale arsenic slag contaminated site based on an integrated model and multi-source environmental data [J]. Environmental Pollution, 2020, 267:115631 Fathizad H, Ali Hakimzadeh Ardakani M, Heung B, et al. Spatio-temporal dynamic of soil quality in the central Iranian desert modeled with machine learning and digital soil assessment techniques [J]. Ecological Indicators, 2020, 118:106736 贾晓琳. 区域土壤重金属污染的源汇空间分析和时空模拟研究[D]. 杭州:浙江大学, 2020:78-80 Jia X L. Source-sink spatial analysis and spatio-temporal simulation of soil heavy metal pollution in regional scale [D]. Hangzhou:Zhejiang University, 2020:78 -80(in Chinese)
Zhao W H, Ma J, Liu Q Y, et al. Accurate prediction of soil heavy metal pollution using an improved machine learning method:A case study in the Pearl River Delta, China [J]. Environmental Science & Technology, 2023, 57(46):17751-17761 许洋, 陈健松, 王志栋, 等. 基于多源异构数据的典型场地土壤重金属污染模拟预测研究[J]. 环境科学学报, 2023, 43(9):357-368 Xu Y, Chen J S, Wang Z D, et al. Simulation and prediction research of heavy metal pollution in soil of typical sites based on multi-source heterogeneous data [J]. Acta Scientiae Circumstantiae, 2023, 43(9):357-368(in Chinese)
Ban M J, Lee D H, Shin S W, et al. Identifying the acute toxicity of contaminated sediments using machine learning models [J]. Environmental Pollution, 2022, 312:120086 Sperlea T, Schenk J P, Dreßler H, et al. The relationship between land cover and microbial community composition in European Lakes [J]. The Science of the Total Environment, 2022, 825:153732 -
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