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英文原文Development of a Decision Support System for Groundwater Pollution Control at Coal-mining Contaminated SitesXiaodong Zhang/Faculty of EngineeringUniversity of Reginaemail: zxd@env.uregina.caChristine W. Chan/ Faculty of Engineering / Energy Informatics Laboratory University of Regina email: Christine.Chan@uregina.caGordon Huang /Faculty of Engineering University of Regina email:gordon.huang@uregina.caAbstract:Groundwater contamination is one of the major environmental concerns at coal-mining sites. Highly saline or highly acidic water from coal-mining can introduce serious pollution to groundwater and adversely affect its quality. This impact may last a long time even after the mining activity has ceased. Identification of an appropriate remediation technique is critical for effective pollution control. However, due to complexity of considerations involved in the pollution, it is difficult for environmental managers to select optimal techniques. This paper presents a robust decision support system named GCDSS that integrates the functional components of mine characterization, numerical modeling, risk assessment and remediation-technique selection. The results from a case study indicated this system can help improve efficiencies of groundwater pollution control at coal-mining contaminated sites.Keywords: decision support system, acid mine drainage, groundwater, coal mine1. IntroductionGroundwater contamination is one of the major environmental concerns at coal mining sites. Acid mine drainage (AMD) is the primary problem associated with pollution from coal mining. AMD is often highly acidic water rich in heavy metals, which can introduce serious pollution to groundwater and adversely affect its quality. A variety of AMD treatment technologies and groundwater remediation methods were developed. Due to the complexities of these technologies, it is often difficult for environmental managers to make optimal decisions in treating specific sites. Decision support systems (DSS) can assist in solving this problem. Many DSSs have been proposed for managing coal mining operations and groundwater remediation. However, there is a lack of study that combines the functions of mine characterization, numerical modeling, risk assessment and remediation technique selection within a DSS. The objective of this study is to address this gap in previous researches and develop an integrated decision support system (GCDSS) that supports all these functions for groundwater pollution control at coal-mining contaminated sites.2. Background: AMD and its treatmentAMD from coal mining is a difficult and costly problem. It can seriously affect groundwater quality and cause metals to leach from mine wastes. AMD results from the oxidation of metal sulfides, particularly pyrite (FeS2). Under the acidic conditions, oxidation of pyrite occurs in the following reaction [1]: FeS2 + 14Fe3+ 8H2O→15Fe2+ + 2SO42- + 16H+ (1)This reaction demonstrates the polluting capability of the oxidation of pyrite that every mole of pyrite can be converted to 16 moles of hydrogen and 2 moles of sulfate. Much acid is generated through this reaction.There are two methods for treating AMD: active treatment and passive treatment. Active treatment involves neutralizing acid-polluted water with alkaline chemicals which include limestone, hydrated lime, caustic soda, soda ash, and ammonia [2]. Active treatment is expensive and requires much time and manpower to maintain. Passive treatment employs naturally occurring chemical and biological reactions and requires little or no maintenance. Passive methods include anoxic drains, limestone rock channels, alkaline recharge of groundwater, and diversion of drainage through man-made wetlands or other settling structures.3. Development of Decision Support System3.1 Knowledge AcquisitionKnowledge acquisition is a bottleneck in DSS development and involves the processes of knowledge elicitation, analysis and representation. It is crucial because output of the system is only as good as the input. The main sources of knowledge in this study are the domain experts, the statistical data about coal mining, and documents.3.2 GCDSSGCDSS consists of the modules for mine characterization, numerical modeling, risk assessment, and remediation technique selection. It also consists of a graphical user interface which allows the user to input and query the site related data, and shows the recommendations and suggestions for the user. Details on the numerical modeling, risk assessment, and remediation technique selection modules are discussed as follows. The architecture of GCDSS is shown in Figure 1.3.2.1 Mine Characterization ModuleMine characterization is crucial for the following numerical modeling, risk assessment, and the selection of remediation technologies in GCDSS. This module has the function of providing the necessary data and standards input for the other three modules. A number of factors on mine characterization are discussed in this module, for example:(1) Types of miningThere are two types of coal mines: surface and underground. Surface mining includes open pit mining, highwall or strip mining, which recovers coal at or close to the earth’s surface. Underground mining extracts coal from under the surface.(2) Mining wastesThe major wastes from coal mining activities are mining water and waste rock, which are serious long-term sources of groundwater deterioration. Mining water, commonly referred to AMD, is highly acid water rich in heavy metals. Mining water can directly pollute groundwater when mining is below the water table, or indirectly through seepage. Waste rock is often disposed in large dumps. When water (such as rainwater, surface water or mining water) infiltrates through waste dumps into subsurface water, groundwater quality can be also greatly affected [3].3.2.2 Numerical Modeling ModuleNumerical modeling of groundwater flow and transport requires a number of data inputs on soil hydraulic properties, time integration parameters, initial and boundary conditions, porous media dispersivities, species solubility, and other many parameters. This module implements the general multicomponent transport equation which can be expressed as follows [4].where θm and θim ?are the fractions of the soil filled with mobile and immobile water respectively; Cwm and Cwim are the concentrations of contaminant w in the mobile and immobile water respectively [ML-3]; qi is the Darcy velocity [LT-1]; Pwm and Pwim are adsorbed phase concentrations of contaminant w in the mobile and immobile phase respectively [MM-1]; f is the fraction of sorption sites which is in direct contact with mobile liquid; ??is soil bulk density [ML-3]; q s is the volumetric flow rate of fluid injection (or withdrawal) per unit volume of the porous medium [L3T-1]; ws C is the concentration of contaminant w in the injected fluid [ML-3]; and Dij is the hydrodynamic dispersion tensor [L2T-1].3.2.3 Risk Assessment ModuleEnvironmental risk is the probability of injury, disease or death under carcinogen and noncarcinogen circumstances [5]. Assessment of the risk of pollution of groundwater includes: simulation for the fate and transport of contaminants in groundwater, assessment of leaching from waste products or polluted soil, analysis of toxicological effects on health and environment, and exposure assessment. Two methods for risk assessment were recommended by USEPA (1992) [6]: excess lifetime cancer risk (ELCR) for cancer-driven pollutants, and hazard quotient (HQ) for noncancer-driven pollutants.(1) Excess Lifetime Cancer Risk (ELCR)ELCR is estimated as the incremental probability of an individual developing cancer over a lifetime as a result of exposure to the potential carcinogen. It may be expressed as follows: ELCR = CDI ??SF (3)where CDI is chronic daily intake (mg/kg?day), SF is the slope factor which is a maximum estimate of the probability of an individual developing cancer over a lifetime of exposure to a particular level of a potential carcinogen. In this study, CDI may be obtained from the equation (4), based on the concentration of contaminant win groundwater [7]. CDI = CW·?IR·EF ·ED/ (AT ·?BW) (4)where CW is the concentration of contaminant win groundwater (mg/L), IR is human ingestion rate (L/day), EF is exposure frequency (days/year), ED is average exposure duration (year), AT is average time (AT = 365 ??days/year ??ED), and BW is body weight (kg). In this study, the values for these parameters for an adult may be: IR= 2 L/day, EF = 350 days/year, ED =70 years (lifetime), AT=365 ??days/year ??70 years, BW = 70 kg.(2) Hazard Quotient (HQ)HQ is used to describe the potential for noncarcinogenic toxicity, and may be expressed as follows:HQ = CDI/RfD (5)where RfD is reference dose (mg/kg?day). The greater the value of HQ, the greater the level of concern. For example, the value 0.05 of HQ indicates that the probability of getting a health injury is 5%. However, the level of concern does not increase linearly as the RfD is approached or exceeded because RfD does not have the same accuracy or precision as the level of concern and is not based on the same severity of toxic effects [7].3.2.4 Remediation-Technique Selection ModuleA number of technologies are available to remediate groundwater contaminated by coal-mining activities. Groundwater remediation methods can be classified into two classes: in situ and ex situ methods. In situ methods treat polluted groundwater in place, while ex situ methods excavate contaminants and transport them off-site for treatment. The methods for treating AMD may be active and passive. Since it is difficult for the user to select a suitable remediation technique for the specific sites, the decision support system can support the decision making process. The user can input the required data such as site characteristics and the parameters for numerical simulation through the friendly user interface. GCDSS can evaluate various combinations of remediation techniques and AMD treatment methods and identify an optimal strategy for groundwater pollution control at a specific coal-mining site.4. ConclusionsIn this study, an integrated decision support system (GCDSS) is proposed for groundwater pollution control at coal-mining contaminated sites. Through the developed GCDSS, the functions of mine characterization, numerical modeling, risk assessment and remediation-technique selection are effectively integrated. The user can access various resources within this system and obtain support on selection of different remediation technologies.References[1] Bonnissel-Gissinger, Pascale, Marc Alnot, Jean-Jacques Ehrhardt, and Philippe Behra, “Surface Oxidation of Pyrite as a function of pH”, Environmental Science and Technology, 32, 2839-2845, 1998[2] U.S. Department of the Interior (USDI)　, Office of Surface Mining, “Acid Mine Drainage Treatment Techniques and Costs”, 2002. Available at: http://www.osmre.gov/amdtcst.htm[3] U. S. Environmental Protection Agency (USEPA), “Abandoned mine site characterization and cleanup handbook”, EPA 910-B-00-001, EPA Region 10, Seattle, Washington, 2000[4] van Genuchten , M. Th., and Wierenga , P. J., “Mass transfer studies in sorbing media 1. Analytical solutions.” Soil Science Society of America Journal, 40, 473-480, 1976[5] Z. Chen, G. H. Huang, and A. Chakma , “Hybrid fuzzy-stochastic modeling approach for assessing environmental risks at contaminated groundwater systems”, Journal of Environmental Engineering, 129, 79-88, 2003[6] U. S. Environmental Protection Agency (USEPA), “Guidelines for exposure assessment”, Federal Register, 57 (104), 22888-22938, 1992[7] U. S. Environmental Protection Agency (USEPA), “Risk assessment guidance for superfund: Volume 1-human health evaluation manual (Part A)”, EPA/540/1-89/002, Office of Emergency and Remedial Response, Washington, D. C., 1989 中文譯文控制煤炭開采位置處的地下水污染的決策支持系統(tǒng)的發(fā)展張曉東/勒吉那大學工程系email : zxd@env.uregina.ca克里斯廷 W. Chan /勒吉那工程大學 / 能源大學信息實驗室email :Christine.Chan@uregina.ca戈登黃/勒吉那大學學部email : gordon.huang @ uregina.ca摘 要：地下水污染是一個主要環(huán)境問題,在煤炭開采地點。高鹽或高酸性水從采煤能引進嚴重污染地下水,并嚴重影響其質(zhì)量。 這種影響可能持續(xù)很長的時間,甚至一直持續(xù)到采礦活動結束以后。確定適當?shù)难a救技術是有效控制污染的關鍵。然而,由于考慮到污染的復雜因素,也很難為環(huán)境管理優(yōu)選技術。 本文獻給出了一套強有力的決策支持系統(tǒng)命名為GCDSS，它集多種功能部件于一體,包括礦井表征 數(shù)值模型,風險評估和修復 -技術選擇。 結果從一個個案例研究表明，該系統(tǒng)可幫助提高控制由于煤炭開采所造成該影響區(qū)域的地下水污染的效率。關 鍵 字: 決策支持系統(tǒng)，礦井污水的排放、地下水, 煤炭開采1 引言在煤炭開采地點的地下水污染是一個主要環(huán)境問題。礦井排放酸性污水(AMD) 是主要的污染源。礦井污水通常是較高濃度酸性的富含重金屬的水,它能侵入地下水，并嚴重的污染，惡化地下水的水質(zhì)。各種礦井污水處理技術和地下污染整治技術已發(fā)展到一定程度。由于這些技術比較復雜, 它一般很難在特定的地點找出治理環(huán)境最佳的方法。決策支持系統(tǒng)( DSS )可幫助解決這一問題。許多( DSS )已經(jīng)提出管理煤炭開采作業(yè)及地下水污染整治。然而，問題是缺少在判定體系(DSS)里與研究相結合的礦井特征參數(shù)、數(shù)值模擬、風險評估和修復技術選擇的研究。這項調(diào)查的目的是為了解決這一差距,在以往的研究與發(fā)展綜合決策支持系統(tǒng) ( gcdss ) ,支持在煤炭污染的地點所有這些活動對地下水污染的控制 。2 背景: AMD 和它的危害煤礦的礦井排放的酸性礦井污水（AMD）的問題，是一個既困難又耗費金錢的問題。 它能嚴重地影響地下水的水質(zhì)，而且導致金屬從礦井廢物 中溶解。AMD來源于金屬質(zhì)硫化物的氧化, 尤其是黃鐵礦 (FeS2). 在酸性條件下，黃鐵礦的氧化在下列的反應如式 [1] 中所示: FeS2 + 14Fe3+ 8H2O→15Fe 2+ + 2SO42- + 16H+ (1)此反應，顯示出每個摩爾的 FeS2 被轉(zhuǎn)換成 2 個摩爾的硫酸和 16 個摩爾的氫。許多酸雨現(xiàn)象都是通過這個反應形成的。有二個方法可以處理 AMD（酸性礦井污水）：積極的處理方式和消極的處理方式。積極的處理方式涉及中和酸性污染水用堿的化學反應，其中包括石灰石、熟石灰、燒堿、純堿（腐蝕劑蘇打）和氨等堿性化學藥品 [2]。積極的處理手段需要大量的才力、人力和時間來維持。消極的處理方法是利用純自然發(fā)生化學反應和生物化學反應來中和酸性污水，而且這種方法需要很少的維持費用甚至達到零費用。靜態(tài)的方法包括缺氧水溝，石灰石渠道，堿性的地下水，和疏導渠通過人造凈化水池或其它沉淀設施，依靠堿性再生和酸根離子轉(zhuǎn)移來中和處理污水。3 支持決策系統(tǒng)的發(fā)展3.1理論知識的獲取理論知識的獲取是DSS開發(fā)的一個瓶頸，并涉及工序引出的知識、分析和描述的流程。因為系統(tǒng)的輸出只能像輸入的一樣，所以這是必要的。該研究的理論的主要來源是專家領域的關于煤礦開采統(tǒng)計的數(shù)據(jù)、和文件。3.2 GCDSS（地下水支持決策系統(tǒng)）GCDSS 是由數(shù)字的模型，危險評估和在調(diào)控技術的選擇等組件組成，以此作為礦井特征的描述。它也由一個友好的用戶界面組成，這個界面允許用戶輸入數(shù)據(jù)和查詢網(wǎng)站的相關數(shù)據(jù)，并向使用者提出忠告和建議。詳細的數(shù)值模擬,風險評估及修復技術選擇單元描述如下. GCDSS 的結構體系如圖1所示：3.2.1礦井開挖的特征參數(shù)組件礦井開挖的特征參數(shù)對GCDSS 的下列數(shù)字的模型，危險評估和修復技術的選擇是決定性的。該模塊有為另外三個組件提供必需的數(shù)據(jù)和標準輸入的功能。礦井開挖的特征參數(shù)上的一些因素在這一個組件中進行分析, 舉例來說：⑴ 煤礦的類型煤礦有二種類型: 地面開采和地下開采。地面采礦（煤層就在地表或埋藏深度在接近地表）包括開方式的深坑采礦、邊坡開采（露天采礦未開采的工作面）或者露天采礦。 地下采礦是在表下進行煤炭開挖的。 圖1 GCDSS 結構體系⑵礦業(yè)廢料來自煤礦開采活動的主要廢棄物是礦井污水和廢棄的矸石,這是長期嚴重影響并使地下水惡化的主要污染源。礦井污水,通常被稱為AMD, 是指具有高濃度的酸性并富含重金屬的水。當開采煤炭的位置在地下水位以下的時候，礦井污水可直接地污染地下水, 或間接地通過滲水污染地下水。廢棄的矸石一般在大的矸石場中處理，當水(如雨水、地表水或者礦井水)浸滲過廢棄的矸石場滲到地下水位,地下水的水質(zhì)很可能受到影響 [3]。3.2.2數(shù)字的模型組件地下水在土壤中的流動的數(shù)字模型，需要一些數(shù)據(jù)輸入到土壤凈化的特征參數(shù)中，包括時間時間積分參數(shù)，初始條件和界限條件,多孔滲入的介質(zhì)分散率差，物質(zhì)的可溶性、和其他的許多參數(shù)。 這一個模塊實現(xiàn)了一般的多元傳輸方程如下式[4] ：式中θ m 和θ im表示是分式的土壤充滿流動和不動的水；C wm 和 Cwim 分別表示地在土壤中所含水中的污染物W 集中體積 [毫升 -3]；q i 是達西速度[LT -1]； qwm 和 qwim 是在可移動又不動的狀態(tài)內(nèi)分別處于吸附狀態(tài)污染物 W 的集中間距 [毫米 -1]； f 是與易流動流動直接的連接處吸附系數(shù)；?? 是土壤的松散密度 [毫升 -3]； q s的每一單位體積的介質(zhì) [L3 T-1]： 的流動注入( 或撤退 )的測定體積流程率；r是容重[ml - 3] Cws 是污染物 W 的集中流動的量[ 毫升 -3]；而且D ij 是流體力學的擴散張量 [L2 T-1].面 向 用 戶 的 界 面實 用 模 型礦 井 特 性 參 數(shù) 數(shù) 據(jù) 模 型危 險 性 評 估 污 水 凈 化 技 術 選 擇理 論 基 礎模 型 數(shù) 據(jù) 庫 技 術 數(shù) 據(jù) 庫危 險 性 評 估規(guī) 則 數(shù) 據(jù) 庫 3.2.3風險評估組件此處的危險環(huán)境是指在致癌物質(zhì)和非致癌物質(zhì)影響下所發(fā)生受傷、疾病或死亡的可能性的環(huán)境[5] 。地下水的污染的危險的評估包括：模擬為地下水中污染物的危害程度和流動趨勢,從廢棄的產(chǎn)物的溶解物或污染土壤的估量、對有毒物影響健康和環(huán)境的分析，并顯示出評估結果。（美國環(huán)保局）USEPA(1992)[6]推薦了兩個危險評估的方法：高致癌性終生致癌的污染物和達到危險份額(HQ) 沒有致癌危險的污染物(ELCR)。⑴過量壽命期癌風險(ELCR)ELCR 被評價為由于在某種具有潛在危險的致癌物質(zhì)環(huán)境下暴露而導致終生單因其而致癌的機率逐漸增加的可能性。它可以被表示成下式關系: ELCR = CDI·SF (3)式中 CDI是慢性的每日攝取量(毫克/公斤.天), SF是在一定數(shù)量的具有潛在的致癌物質(zhì)中暴露導致的終生都有可能因這個因素而單獨致癌的可能性的一個最大估計斜率因素。 在這研究，基于地下水中集中的污染物W ，CDI 可由方程 (4)中計算得出。 CDI = CW ??IR·?EF·ED/ (AT·BW) (4)式中 CW 是地下水中的污染物的集中量( 毫克/L) ，IR 是人類的攝取率(L/日) ，EF 是暴露在污染污中的頻率(每天/年) ，ED 是暴露持續(xù)時間(年),AT是平均時間(AT =365×天/年×ED), BW 是人的體重(公斤)。在這研究中，對于一個成人對以上這些參數(shù)值可取: IR=2 L/日子,EF=350天/ 年, ED=70年(終生), AT=365×每天/年×70 年, BW=70 個公斤。⑵ 危險商數(shù) (HQ)HQ 是用來表示非致癌物的毒性潛能, 如下式所示:HQ = CDI/RfD (5)式中 RfD 是參考劑量(毫克/公斤·日子). HQ的值愈大,危險程度也愈較高。舉例來說，HQ 的取值0.05表示健康受到傷害的可能性是5% 。然而 RfD 沒有與擔心程度相同的準確性或精密度，并且不是基于同樣嚴重的毒性危害所以，當 RfD 被接近或者超過線性增長的時候，擔心程度也是非線性地增加[7]。3.2.4地下水在調(diào)控技術的選擇組件多項技術可以補救煤礦開采活動造成的地下水污染。 地下水污染整治方法可被分成兩類：原地處理和場外處理?，F(xiàn)場處理是現(xiàn)場處理受污染地下水,然而場外處理方法是把挖掘出來的污染物運出現(xiàn)場后再進行處理。利用這個方法處理AMD時有可能是積極的也可能是消極的。因為用戶在特定 的位置選擇適當?shù)膬艋夹g是困難的，決策支持系統(tǒng)能支持決策程序。用戶可以輸入必需的數(shù)據(jù)例如；位置特征參數(shù)和數(shù)字的模擬參數(shù)通過友好的用戶者界面進行輸入。 GCDSS 能對在一個特定的煤礦開采位置處的地下水污染進行控制、多種組合的修復技術和AMD 的處理方法等方面作出各種功能不同的多種不同的評估，并且可以確定一個最佳的方案。4 結論（1）在這項研究中，總結了判定系統(tǒng)(GCDSS)在煤礦開采的特定位置，對地下水污染的控制。（2）通過制定 GCDSS 的功能，礦井的特征參數(shù)、數(shù)字模型、危險評估和修復技術技術的選擇有效地被有機的結合起來。（3）用戶能在不同修復技術的選擇上存取各種不同的該系統(tǒng)里面的資源并能獲得支持。參考文獻：[1] 邦尼斯爾-吉辛、帕斯卡爾，馬可-艾倫特，珍-雅克 依哈德 ， 菲利—貝哈," 升至水面黃鐵礦的氧化作為一個酸堿質(zhì)的功能 ", 環(huán)境科學和技術, 32,2839-2845,1998[2] 美國內(nèi)政部 (USDI) ，地表采礦辦公室, " 礦井酸性污水的治理技術和費用 ", 2002. http://www.osmre.gov/amdtcst.htm[3] U. S. 環(huán)保署 (USEPA), " 粗獷型挖掘位置的描述和清除手冊 ", 環(huán)保署 910 B-00-001 , 環(huán)保署區(qū)域 10 、西雅圖，華盛頓, 2000[4] 萬 Genuchten,M. Th。, 韋恩戈， P. J., "彌撒移動在吸收媒介 1 可溶物解析。" 土壤科學協(xié)會的美國日記, 40,473-480,1976[5] Z. 陳 , G. H. 黃， A. 查可馬 ， " 在受污染的地下水系統(tǒng)評估環(huán)境的危險的混合、模糊-隨機程序的模型方法 " ，環(huán)境工程學的日記, 129,79-88,2003[6] U. S. 環(huán)保署 (USEPA) ， " 暴露評估的指導方針 " ，聯(lián)邦的寄存器, 57(104), 22888-22938,1992[7] U. S. 環(huán)保署 (USEPA), "危險評估次要投資指導 : 第 1 冊-人類的健康評估手冊 (部份 A)", 環(huán)保署/540/1-89/002, 緊急和處理效果、華盛頓， D. C. 的辦公室, 1989 致 謝在美麗的中國礦業(yè)大學度過的這四年，是我這一生中最難忘的四年，也是非常寶貴的四年，這個機會來之不易，讓我倍加珍惜。在這段時間里我感到過的很充實，有了奮斗方向和目標。在這里讓我開闊了眼界，見識到名師、名校的風范。我們即將離開這美麗的校院，說句實話，我還真舍不得。我舍不得離開可敬的老師、親愛的同學，舍不得這里的圖書館、操場，食堂，教室，綠地，宿舍和這里的一草一木。四年的時間很快就到了，四年中我在老師們的教育、同學們的幫助和自己的努力下即將完成我的本科學習，在四年的學習過程中，是因為有我的老師、親人與同學的大力支持和幫助，才使我能夠順利完成學業(yè)。值此畢業(yè)論文完成之際，謹向他們表示我最真摯的謝意與衷心的祝福。在經(jīng)過近半年的準備，實習和三個多月的認真設計，終于完成了我的畢業(yè)論文。在次我特別感謝曹勝根老師對我的悉心指導，鄒老師為本論文的順利完成提供了大力支持和耐心的知道，同時鄒老師嚴謹治學的態(tài)度、深厚的專業(yè)功底和勤奮求實的工作作風給我留下了難忘的印象。老師為人師表，使我受到了深刻的教育和啟迪，并將成為我終生受益的寶貴財富。同時我還要感謝學院領導和輔導員老師給予我們畢業(yè)生的無私的幫助，是學院為我們提供了良好的學習環(huán)境和便利的條件，還有機房老師們的大力支持，沒有你們辛勤的汗水就不會有我們的今天，在此我衷心感謝您們的關心和幫助！在此還要衷心感謝與我同組進行設計的同學，在整個實習與設計的過程中，一起討論、學習和進步，他們給了我很大的幫助和關心，解決了在設計過程中所遇到的許多難題。最后，衷心的感謝在我四年的學習中，所有給予我關心、支持和鼓勵的老師和同學們！