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Volume 38 Issue 6
Aug.  2020
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Article Navigation >  ENVIRONMENTAL ENGINEERING  > 2020  >  38(6): 252-258
WANG Xing-run, LI Lei, YANG Xiang-hua, TIAN Yong-qiang. PROGRESS IN REMEDIATION OF CHROMIUM-CONTAMINATED SITES[J]. ENVIRONMENTAL ENGINEERING , 2020, 38(6): 1-8,23. doi: 10.13205/j.hjgc.202006001
Citation: JIA Ling-hui, ZHENG Shi-hao, SUN Li-hui, BAO Yong-ming. SCREENING OF COLD-ADAPTED PETROLEUM DEGRADING BACTERIA AND CHARACTERIZING MICROFLORA FOR PETROLEUM DEGRADATION[J]. ENVIRONMENTAL ENGINEERING , 2020, 38(6): 252-258. doi: 10.13205/j.hjgc.202006041
shu

SCREENING OF COLD-ADAPTED PETROLEUM DEGRADING BACTERIA AND CHARACTERIZING MICROFLORA FOR PETROLEUM DEGRADATION

doi: 10.13205/j.hjgc.202006041

  • 1. School of Food and Environment Science and Technology, Dalian University of Technology, Panjin 124221, China;

  • 2. School of Life Science and Biotechnology, Dalian University of Technology, Dalian 116024, China

  • Received Date: 2019-06-11
    Abstract
  • The performance of in-situ bio-remediation of petroleum-contaminated soils has been always unsatisfactory, because of complex composition of crude oil and its strong biological toxicity, as well as low microbial activity at low soil temperature. In this paper, 7 cold-adapted oil-degrading bacteria strains were screened and identified from oil polluted soils. Based on the degrading characteristics of the 7 bacteria strains for petroleum composition, 6 cold-adapted oil-degrading microfloras were prepared. The CO2 production and O2 consumption of 6 microfloras for degrading crude oil in 5 L fermenters were monitored online with a gas analyzer. The most efficient microflora, consisted of Arthrobacter sp. JLH 001, Acinetobacter baumannii JLH 002, Pseudomonas fragi JLH 003 and Arthrobacter sp. JLH 006, showed maximal O2 consumption and CO2 production capacity after about 48 h, and completely degraded crude oil (with content of 1%) after about 72 h at 15 ℃, and the degradation was significantly accelerated at 25 ℃. These results suggested that efficient in-situ bio-remediation of petroleum-contaminated soil could be realized by adding cold-adapted oil-degrading microfloras.
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    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 8.0 %其他: 8.0 %其他: 0.1 %其他: 0.1 %Central District: 0.1 %Central District: 0.1 %China: 1.2 %China: 1.2 %Japan: 0.1 %Japan: 0.1 %Saitama: 0.1 %Saitama: 0.1 %Tuen Mun San Hui: 0.3 %Tuen Mun San Hui: 0.3 %United States: 0.3 %United States: 0.3 %[]: 0.6 %[]: 0.6 %上海: 5.5 %上海: 5.5 %东莞: 1.1 %东莞: 1.1 %中山: 0.1 %中山: 0.1 %临汾: 0.1 %临汾: 0.1 %临沂: 0.3 %临沂: 0.3 %丽水: 0.1 %丽水: 0.1 %丽江: 0.1 %丽江: 0.1 %乌兰察布: 0.1 %乌兰察布: 0.1 %乐山: 0.1 %乐山: 0.1 %佛山: 0.4 %佛山: 0.4 %保定: 0.6 %保定: 0.6 %信阳: 0.1 %信阳: 0.1 %兰州: 0.1 %兰州: 0.1 %凉山彝族自治州: 0.1 %凉山彝族自治州: 0.1 %北京: 11.5 %北京: 11.5 %十堰: 0.1 %十堰: 0.1 %南京: 3.5 %南京: 3.5 %南充: 0.3 %南充: 0.3 %南宁: 0.2 %南宁: 0.2 %南昌: 1.1 %南昌: 1.1 %南通: 0.2 %南通: 0.2 %南通市崇川区: 0.1 %南通市崇川区: 0.1 %厦门: 0.5 %厦门: 0.5 %台北: 0.3 %台北: 0.3 %台州: 0.6 %台州: 0.6 %合肥: 1.2 %合肥: 1.2 %吉林: 0.4 %吉林: 0.4 %呼和浩特: 0.1 %呼和浩特: 0.1 %咸阳: 0.1 %咸阳: 0.1 %哈尔滨: 0.1 %哈尔滨: 0.1 %唐山: 0.2 %唐山: 0.2 %嘉兴: 0.1 %嘉兴: 0.1 %大同: 0.1 %大同: 0.1 %天津: 2.9 %天津: 2.9 %太原: 0.8 %太原: 0.8 %威海: 0.1 %威海: 0.1 %娄底: 0.1 %娄底: 0.1 %宁波: 0.4 %宁波: 0.4 %安庆: 0.1 %安庆: 0.1 %安康: 0.1 %安康: 0.1 %安顺: 0.1 %安顺: 0.1 %宜昌: 0.1 %宜昌: 0.1 %宜春: 0.6 %宜春: 0.6 %宝鸡: 0.1 %宝鸡: 0.1 %宣城: 0.6 %宣城: 0.6 %宫城: 0.1 %宫城: 0.1 %巴中: 0.1 %巴中: 0.1 %常州: 0.6 %常州: 0.6 %常德: 0.3 %常德: 0.3 %平顶山: 0.1 %平顶山: 0.1 %广州: 1.2 %广州: 1.2 %廊坊: 0.1 %廊坊: 0.1 %延安: 0.1 %延安: 0.1 %张家口: 1.3 %张家口: 1.3 %德州: 0.1 %德州: 0.1 %德阳: 0.1 %德阳: 0.1 %惠州: 0.2 %惠州: 0.2 %成都: 1.3 %成都: 1.3 %成都市双流区: 0.1 %成都市双流区: 0.1 %扬州: 0.3 %扬州: 0.3 %抚州: 0.1 %抚州: 0.1 %拉萨: 0.1 %拉萨: 0.1 %拉贾斯坦邦: 0.1 %拉贾斯坦邦: 0.1 %攀枝花: 0.1 %攀枝花: 0.1 %新乡: 0.3 %新乡: 0.3 %无锡: 0.5 %无锡: 0.5 %昆明: 0.8 %昆明: 0.8 %晋城: 0.1 %晋城: 0.1 %朝阳: 0.2 %朝阳: 0.2 %杭州: 3.9 %杭州: 3.9 %枣庄: 0.1 %枣庄: 0.1 %株洲: 1.0 %株洲: 1.0 %桂林: 0.4 %桂林: 0.4 %榆林: 0.1 %榆林: 0.1 %武汉: 2.6 %武汉: 2.6 %汕头: 0.1 %汕头: 0.1 %沈阳: 0.5 %沈阳: 0.5 %河源: 0.1 %河源: 0.1 %泸州: 0.1 %泸州: 0.1 %洛阳: 0.1 %洛阳: 0.1 %济南: 1.3 %济南: 1.3 %济源: 0.1 %济源: 0.1 %海口: 0.1 %海口: 0.1 %淄博: 0.4 %淄博: 0.4 %淮北: 0.1 %淮北: 0.1 %深圳: 0.7 %深圳: 0.7 %温州: 0.5 %温州: 0.5 %湖州: 0.4 %湖州: 0.4 %湘潭: 0.1 %湘潭: 0.1 %漯河: 0.7 %漯河: 0.7 %潍坊: 0.1 %潍坊: 0.1 %潮州: 0.1 %潮州: 0.1 %濮阳: 0.1 %濮阳: 0.1 %烟台: 0.3 %烟台: 0.3 %眉山: 0.1 %眉山: 0.1 %石家庄: 1.0 %石家庄: 1.0 %福州: 0.8 %福州: 0.8 %绍兴: 0.3 %绍兴: 0.3 %绵阳: 0.4 %绵阳: 0.4 %芒廷维尤: 5.9 %芒廷维尤: 5.9 %芝加哥: 1.1 %芝加哥: 1.1 %苏州: 0.6 %苏州: 0.6 %葫芦岛: 0.1 %葫芦岛: 0.1 %衡水: 0.1 %衡水: 0.1 %衡阳: 0.2 %衡阳: 0.2 %衢州: 0.2 %衢州: 0.2 %襄阳: 0.1 %襄阳: 0.1 %西宁: 4.7 %西宁: 4.7 %西安: 1.5 %西安: 1.5 %贵阳: 0.2 %贵阳: 0.2 %赣州: 0.2 %赣州: 0.2 %达州: 0.3 %达州: 0.3 %运城: 0.9 %运城: 0.9 %遵义: 0.2 %遵义: 0.2 %邯郸: 0.1 %邯郸: 0.1 %邵阳: 0.1 %邵阳: 0.1 %郑州: 1.7 %郑州: 1.7 %鄂州: 0.1 %鄂州: 0.1 %重庆: 2.0 %重庆: 2.0 %金华: 0.1 %金华: 0.1 %银川: 0.1 %银川: 0.1 %锦州: 0.4 %锦州: 0.4 %镇江: 0.1 %镇江: 0.1 %长春: 0.4 %长春: 0.4 %长沙: 3.2 %长沙: 3.2 %长治: 0.3 %长治: 0.3 %阜新: 0.1 %阜新: 0.1 %阳泉: 0.1 %阳泉: 0.1 %陇南: 0.1 %陇南: 0.1 %青岛: 2.5 %青岛: 2.5 %韶关: 0.1 %韶关: 0.1 %香港特别行政区: 0.3 %香港特别行政区: 0.3 %鹰潭: 0.1 %鹰潭: 0.1 %黄冈: 0.1 %黄冈: 0.1 %黄石: 0.6 %黄石: 0.6 %齐齐哈尔: 0.1 %齐齐哈尔: 0.1 %其他其他Central DistrictChinaJapanSaitamaTuen Mun San HuiUnited States[]上海东莞中山临汾临沂丽水丽江乌兰察布乐山佛山保定信阳兰州凉山彝族自治州北京十堰南京南充南宁南昌南通南通市崇川区厦门台北台州合肥吉林呼和浩特咸阳哈尔滨唐山嘉兴大同天津太原威海娄底宁波安庆安康安顺宜昌宜春宝鸡宣城宫城巴中常州常德平顶山广州廊坊延安张家口德州德阳惠州成都成都市双流区扬州抚州拉萨拉贾斯坦邦攀枝花新乡无锡昆明晋城朝阳杭州枣庄株洲桂林榆林武汉汕头沈阳河源泸州洛阳济南济源海口淄博淮北深圳温州湖州湘潭漯河潍坊潮州濮阳烟台眉山石家庄福州绍兴绵阳芒廷维尤芝加哥苏州葫芦岛衡水衡阳衢州襄阳西宁西安贵阳赣州达州运城遵义邯郸邵阳郑州鄂州重庆金华银川锦州镇江长春长沙长治阜新阳泉陇南青岛韶关香港特别行政区鹰潭黄冈黄石齐齐哈尔

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      沈阳化工大学材料科学与工程学院 沈阳 110142

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