AEBA工艺技术在煤气厂废水处理中的应用

大同煤矿集团公司煤气厂于 1989年建成 40门 82伍型连续直立炭化炉，后又增建水煤气两段炉，煤气产量由 0.135 Mm3/d增加至 0.275 Mm3/d。工业污水中主要污染物为 COD、酚、氰化物、氨氮和油等。该厂原建有一期和二期工业废水处理系统，但由于工艺落后，处理后的废水不能达标排放，故常与附近农户发生纠纷。 1997年该厂采用的 AEBA工艺技术投入运行，在预处理、萃取和生化部分运行正常情况下，二沉池出水中各种污染物指标均较低，再经过活性炭柱处理后， COD、挥发酚、氨氮、油、悬浮物、色度各项指标均能达标。 AEBA工艺在处理煤气厂焦化废水上是成功的，而且具有节约稀释水，回收酚钠盐等优点，在同类废水处理中具有推广价值。 1 焦化废水原治理情况 1.1 焦化废水水质 大同煤矿集团公司煤气厂焦化过程中产生的废水主要有：剩余氨水、煤气管道冷凝水、焦油贮存槽分离水等多种废水，每天总排放废水约 2 000 t，污水中主要污染指标是 COD 2 000～ 3 000 mg/L，油 1 000～ 1 500 mg/L，酚 3 000～ 4 000 mg/L， BOD510 000 mg/L左右，氨氮约 1 500 mg/L，悬浮物约 1 500～ 2 000 mg/L， pH值 8.9～ 9.3。

Spatial and Temporal Variation of Particulate Matter (PM10 and PM2.5) and Its Health Effects during the Haze Event in Malaysia

This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries.Daily PM concentrations were analysed for urban and industrial areas including Alor Setar,Tasek,Shah Alam,Klang,Bandaraya Melaka,Larkin,Balok Baru,and Kuala Terengganu in 2018 and 2019.The analysis employed spatiotemporal to examine how PM levels were distributed.The data summary revealed that PM levels in all study areas were right-skewed,indicating the occurrence of high particulate events.Significant peaks in PM concentrations during haze events were consistently observed between June and October,encompassing the south west monsoon and inter-monsoon periods.The study on acute respiratory illnesses primarily focused on Selangor.Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma(AEBA)and acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with values of 260.500 and 185.170,respectively.Similarly,for outpatient cases of AEBA and AECOPD,Klang had the highest average values of 41.67 and 14.00,respectively.Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning.The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions,particularly from June to September,as shown in the bar diagram.Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses,seen in higher inpatient and outpatient visits(p<0.05).However,seasonal variability had minimal impact on healthcare utilization.These findings offer a comprehensive assessment of PM levels during historic haze episodes,providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.

基于预测能力的扩展极限边界分析法

本文在传统EBA方法的基础上,将其引入到时间序列中,构建以预测为导向的AEBA模型选择方法。AEBA在模型选择上更注重于模型的预测能力,在稳健性检验上细分为模型稳健性检验与参数稳健性检验两部分,提出了基于时间序列预测能力的检验方法。最后实证示例用AEBA方法对影响石油股票指数收益率的因素进行了研究,表明该方法选择的模型的预测能力,特别是短期预测能力要显著强于CAPM、三因子模型、ARMA以及VAR。