地震高概率区域潜在重金属面源污染风险评价

杨妍

doi:10.3799/dqkx.2017.116

地震高概率区域潜在重金属面源污染风险评价

doi: 10.3799/dqkx.2017.116

杨妍

武汉大学资源与环境科学学院，湖北武汉 430079

基金项目:

国家自然科学基金项目 41301585

详细信息

作者简介:
杨妍(1983-)，女，讲师，博士，从事地理信息科学研究和相关教学工作，主要从事灾害、环境及GIS大数据研究

中图分类号: P65
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出版历程
- 收稿日期: 2017-01-25
- 刊出日期: 2017-10-18

Evalution on High Pobabilistic Seismic-Led Heavy Metal Non-Point Source Pollution

Yang Yan

School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China

摘要

摘要: 地震的不易预见性易导致突发性环境污染，目前的相关研究多侧重于地灾发生后的调研评价，对高概率地震灾害区域潜在重金属面源污染风险预评价的研究尚有限，而预风险评价能为制定有效措施以降低灾害污染程度提供重要参考信息.为初探地震所致突发性重金属面源污染的风险预评估方法，基于地震峰值加速度因素结合建筑破损因素、潜在重金属污染物负荷值以四川省和重庆市为例构建潜在重金属面源污染及人口暴露风险评价模型.结果表明，研究区域的11个子流域受到潜在重金属面源污染风险，其中六价铬涉及子流域最多.不考虑人口暴露时，六价铬引发风险主要分布于研究区域东北角、中部及中南部，其他9种重金属污染物的潜在面源污染区主要分布于四川中南部.考虑人口暴露因素时，则六价铬引发风险主要分布于子流域W1和W2的东南部，其他重金属污染物则集中于子流域W4的北部.以四川省和重庆市为例初探性地建立了基于地震峰值加速度因素的地震引发潜在重金属污染及人口暴露预风险模型.
- 地震 /
- 面源污染 /
- 重金属 /
- 四川省 /
- 重庆市 /
- 工程地质
Abstract: To minimize the unexpected seismic damage, it is significant to evaluate the potantial seismic risk in the high probabilisitic seismic hazard zones and take effective precautionary measures. This paper aims to evaluate the risk of heavy metal non-point source pollution caused by seismic-led industrial building collapse. It is based on the seismic hazard of 10-percent probability of exceedance in 50 years, and the minimum value of the water quality standard in Sichuan, China. The method of Soil Conservation Service (SCS) curve number (CN) was used to compute the daily runoff depth, and to estimate the potential risk state of non-point source heavy metal pollution combined with the seismic damage index and population index. The results indicate: (1) eleven sub-basins are under the potential risk of seismic-led non-point source heavy metal pollution; (2) Compared to other heavy metal pollutants, more sub-basins are under the risk of Cr⁶⁺ pollution, and are mainly distributed in the northeast, central and south central of Sichuan province, whereas high risk subbasins of other heavy metal pollutants are most located in the south central areas of Sichuan province; (3) considering the population index, the high risk areas of Cr⁶⁺ pollution are mainly in the southeast of sub-basins W1 and W2, while those subjected to pollution of other heavy metals are mostly in the north of sub-basin W4.
- earthquake /
- non-point /
- heavy metal /
- Sichuan /
- Chongqing /
- engineering geology

HTML全文

图 1 四川省及重庆市DEM、PGA、土地利用、水系分布、降雨监测站点分布及人口分布等研究数据示意图

Fig. 1. Collected data maps of DEM, PGA, landuse, rivers, rain falls and population

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图 2 研究区域内相关子流域潜在重金属排放工厂站点分布及涉及县市区

Fig. 2. Distribution of studied factories and counties in each sub-basin

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图 3 重点受灾流域的重金属污染物种类分布

Fig. 3. Distribution of heavy metal categories in each sub-basin

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图 4 重点受灾区的每一种水质污染物在不同水域内的分布图(不考虑人口暴露风险)

Fig. 4. The risk distribution (without population factor) of each heavy metal contaminant in study area

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图 5 重点受灾区的每一种水质污染物在不同水域内的分布图(考虑人口暴露风险)

Fig. 5. The risk distribution (with population factor) of each heavy metal contaminant in study area

下载: 全尺寸图片幻灯片

表 1 抗震设防烈度和基本设计地震加速度的对应关系

Table 1. The relationship between seismic intensity and PGA

抗震设设防烈度	6	7	8	9
设计基本地震加速度	0.05 g	0.10(0.15) g	0.20(0.30) g	0.40 g

下载: 导出CSV

表 2 建筑物破坏损失比

Table 2. The damage ration of buildings in five damage states

结构类别	破坏等级(%)
结构类别	基本完好	轻微破坏	中等破坏	严重破坏	毁坏
钢筋混凝土、砌体房屋	0~5	6~15	16~45	46~80	81~100
工业厂房	0~4	5~16	17~45	46~80	81~100
城镇平房、农村建筑	0~5	6~15	16~40	41~70	71~100

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表 3 研究区域土地利用方式的CN值

Table 3. The CN of four hydrologic soil groups in different types of land use

土地利用	A	B	C	D
旱地	61	72	79	82
田地	55	69	78	83
林地	36	60	73	79
草地	45	65	75	80
居民区	62	75	83	87
水域(如冰川等)	98	98	98	98
湿地	77	86	91	94

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表 4 AMC等级划分

Table 4. Grade division of AMC

AMC	土壤湿度状态	近5日降水量(mm)
AMC	土壤湿度状态	休眠期	生长期
Ⅰ	干	＜13	＜36
Ⅱ	中	13~28	36~53
Ⅲ	湿	＞28	＞53

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表 5 相关工厂站点所在的11个子流域的面积、污染物种类个数、承载度以及涉及的县市个数

Table 5. Area size, pollutant categories, density index and number of corresponding counties in each sub-basin

研究区子流域				潜在受灾县(个)
子流域序号	面积(m²)	污染物(个)	承载度(%)	潜在受灾县(个)
W1	1 446 800	1	0.7	14
W2	968 800	1	1.0	11
W3	2 269 600	1	0.4	23
W4	960 900	10	10.4	11
W5	1 186 200	10	8.4	10
W6	451 200	6	13.3	5
W7	1 972 900	6	3.0	27
W8	1 029 800	10	9.7	12
W9	3 226 200	10	3.1	24
W10	2 470 100	8	3.2	40
W11	981 200	5	3.1	18

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