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891.
892.
水文地质参数本身存在不确定性,为分析水文地质参数不确定性对地下水DNAPLs污染多相流数值模拟模型输出结果的影响,本文针对假想算例展开研究,首先建立了研究区地下水DNAPLs污染多相流数值模拟模型;然后,运用灵敏度分析法筛选对模型输出结果影响较大的参数作为随机变量;为减少反复调用多相流模拟模型产生的计算负荷,运用克里格方法建立多相流模拟模型的替代模型,利用替代模型完成蒙特卡洛随机模拟;最后,对随机模拟的结果进行统计分析并完成地下水污染风险评价.结果表明,利用污染物浓度分布函数可以估算单井遭受污染的风险;利用地下水污染风险图可以对全区地下水遭受不同程度污染的风险大小进行分区,为地下水污染防治提供更加科学、丰富的参考依据. 相似文献
893.
Ying Han Wenbin Liu Haifeng Li Rongrong Lei Guorui Liu Lirong Gao Guijin Su 《环境科学学报(英文版)》2018,30(10):208-212
The concentrations and distribution of polychlorinated naphthalenes(PCNs) in the whole blood of eight typical terrestrial meat animals(chicken, duck, rabbit, pig, cattle, sheep,horse and donkey) consumed daily in our life were investigated. The total concentrations(on a liquid volume basis) of PCNs were in a range from 305 to 987 pg/L. Donkey blood contained the highest PCN concentrations. Mono-CNs were the dominant homolog group,accounting for 38%–71% PCNs. Apart from the mono-CNs and tri-CNs homolog groups, two hepta-CNs(mean: 9.5%) contributed most, followed by tetra-CNs(mean: 6.5%). The congeners CN1, 5/7, 24/14, 27/30, 52/60, 66/67, and 73 were the most abundant congeners or congener groups. The highest toxicity equivalencies(TEQs) were observed in cattle blood(117.4 fg TEQ/L) then chicken blood(117.1 fg TEQ/L). CN73 contributed 65% to total TEQs,followed by CN70(20%) and CN66/67(14%). The dietary intakes of PCNs were also estimated.Chicken meat, which forms the second largest component of meat product consumption in China, contributed most to the total TEQs(61%), followed by beef(27%) and pork(5.9%). The consumption of chicken might pose the highest risk from exposure to PCNs than other types of meat to populations who prefer to eat chicken meat. 相似文献
894.
Ting Han Lan Yao Li Liu Aiyong Xian Hui Chen Wenbo Dong Jianmin Chen 《环境科学学报(英文版)》2018,30(9):127-135
As the largest iron and steel producer in China, a part of Baosteel moved out of Shanghai deserves close attention due to its environmental impact. To understand the effect of Baosteel emission control on air quality in Shanghai, daily PM_(10), PM_(2.5), SO_2, NO_2 and CO were measured from 2010 to 2016. Concentrations of pollutants in Baoshan District presented a decreased trend during 2010–2016, with a reduction rate of 28.6% for PM_(10), 67.3% for SO_2, 8.6% for NO_2 and 42.0% for CO. However, fine particle pollution in Baoshan District during 2012–2016 seems to become more prominent, with PM_(2.5) concentration of 47 ± 28,45 ± 33, 38 ± 24, 54 ± 41 and 51 ± 34 μg/m3, respectively, indicating a slight increase of 8.5%in PM_(2.5). Concentrations of PM_(10) and CO decreased by 12.5% and 33.8% in the second half year in 2016(compared with that in 2015) probably due to closure of blast furnace of Baosteel. Baosteel was identified as the largest pollution source in Baoshan District.Emission from Baosteel accounted for 58.0% of SO_2, 43.6% of NO_2 and 79.3% of dust in total emission from Baoshan District during 2010–2015. Meanwhile, pollutant emission and coal consumption from Baosteel decreased by 52.0% for SO_2, 40.1% for NO_2, 15.7% for dust and22% for coal consumption. Energy consumption in Baoshan District reduced by 31% from2011 to 2015. Air quality improvement in Shanghai was attributed to local emission reduction, together with regional air quality improvement. 相似文献
895.
896.
Rui Han Shuxiao Wang Wenhai Shen Jiandong Wang Kang Wu Zhihua Ren Mingnong Feng 《环境科学学报(英文版)》2016,28(8):134-146
The purpose of this study is to analyze the climatic characteristics and long-term spatial and temporal variations of haze occurrence in China. The impact factors of haze trends are also discussed. Meteorological data from 1961 to 2012 and daily PM10 concentrations from 2003 to 2012 were employed in this study. The results indicate that the annual-average hazy days at all stations have been increasing rapidly from 4 days in 1961 to 18 days in 2012. The maximum number of haze days occur in winter (41.1%) while the minimum occur in summer (10.4%). During 1961-2012, the high occurrence areas of haze shifted from central to south and east regions of China. The Beijing-Tianjin-Hebei (Jing-Jin-Ji) region, Shanxi, Shaanxi, and Henan Province are the high occurrence areas for haze, while the Yangtze River Delta (YRD) and the Pearl River Delta (PRD) have become regions with high haze occurrences in the last 25 years. Temperature and pressure are positively correlated with the number of haze days. However, wind, relative humidity, precipitation, and sunshine duration are negatively correlated with the number of haze days. The key meteorological factors affecting the formation and dissipation of haze vary for high and low altitudes, and are closely related to anthropogenic activities. In recent years, anthropogenic activities have played a more important role in haze occurrences compared with meteorological factors. 相似文献
897.
为提高铁碳微电解处理染料废水中CODCr去除率,将Plackett-Burman和Box-Behnken试验设计方法相结合应用于废水处理条件的筛选与优化. Plackett-Burman设计试验结果表明:铁碳比(体积比)、反应时间和曝气量是影响铁碳微电解处理染料废水CODCr去除率的3个关键性因素. Box-Behnken试验设计方法和三维响应面分析表明,铁碳微电解处理染料废水对CODCr去除率的最优化操作条件是铁碳比为3∶2、反应时间为120 min、曝气量为40 L/min. 在该优化条件下,当ρ(CODCr)在1 000~10 000 mg/L之间变化时,CODCr去除率的试验结果均落在模型预测结果的95%置信区间(75.5%~83.3%)内,说明模型能对铁碳微电解处理结果进行良好的预测,因此具有一定的可信度. 相似文献
898.
为更好地解析北京地区ρ(PM2.5)的长期变化特征及气流轨迹聚类分析结果,对2007年8月—2014年7月在中国环境科学研究院实测的ρ(PM2.5)数据进行了统计分析,分析其年际、季节和月际变化特征;通过计算PM2.5的AQI分指数,分析了污染等级的时间变化特征;结合后向气流轨迹,对ρ(PM2.5)年际、季节变化与气团来源的关系进行了分析.结果表明:北京地区2008—2013年ρ(PM2.5)年均值分别为111.5、95.8、94.8、80.5、75.2、81.3 μg/m3,整体呈逐年下降趋势,但污染水平依然较高;ρ(PM2.5)由高到低的季节次序为秋季、冬季、春季、夏季,平均值分别为111.6、94.8、77.2、70.5 μg/m3,PM2.5重污染时段主要出现在秋冬季节,并且冬季ρ(PM2.5)近年来逐渐呈上升趋势;ρ(PM2.5)月均值呈单峰型变化,11月最高(为125.3 μg/m3),7月最低(为76.4 μg/m3);轨迹聚类分析发现,途经山西省北部和河北省南部的气流轨迹中ρ(PM2.5)较高,而来自北方及西北方向的气团相对较清洁,ρ(PM2.5)较低.北京地区近些年实施的大气污染减排措施对于控制PM2.5污染取得了一定效果,但针对秋冬季节重污染过程的控制力度仍需要加强,同时也要注意区域污染传输对北京地区ρ(PM2.5)的影响. 相似文献
899.
900.