Lessons after Bhopal: CSB a catalyst for change

The Bhopal tragedy was a defining moment in the history of the chemical industry. On December 3, 1984, a runaway reaction within a methyl isocyanate storage tank at the Union Carbide India Limited pesticide plant released a toxic gas cloud that killed thousands and injured hundreds of thousands. After Bhopal, industrial chemical plants became a major public concern. Both the public and the chemical industry realized the necessity of improving chemical process safety.

Bhopal served as a wake-up call. To prevent the same event from occurring in the United States, many legislative and industrial changes were invoked—one of which was formation of the U.S. Chemical Safety and Hazard Investigation Board (CSB). The ultimate goal of CSB is to use the lessons learned and recommendations from its investigations to achieve positive change within the chemical industry—preventing incidents and saving lives.

Although it seems clear that the lessons learned at Bhopal have improved chemical plant safety, CSB investigations indicate that the systemic problems identified at Bhopal remain the underlying causes of many incidents. These include:

• Lack of awareness of reactive hazards.

• Lack of management of change.

• Inadequate plant design and maintenance.

• Ineffective employee training.

• Ineffective emergency preparedness and community notification.

• Lack of root cause incident investigations and communication of lessons learned.

The aim of this paper is to present common themes from recent cases investigated by CSB and to discuss how these issues might be best addressed in the future.

This paper has not been independently approved by the Board and is published for general informational purposes only. Any material in the paper that did not originate in a Board-approved report is solely the responsibility of the authors and does not represent an official finding, conclusion, or position of the Board.     

西江年最高水位的神经网络预报模型

对西江洪水发生的特征进行分析表明，洪水发生频率高，具有明显阶段性特征，并与流域面雨量密切相关。利用前期环流场、海表温度（SST）场及环流特征量资料选择初选预报因子，然后对初选预报因子作EOF分解构造综合预报因子，结合人工神经网络方法建立了西江年最高水位预报模型，并对预报模型进行独立样本试验。结果表明，该预报模型对历史样本拟合精度高，试报效果明显好于传统的逐步回归模型，可在汛期预测业务中应用。     

超声波辅助提取杜仲籽油的工艺优化

以杜仲籽为原料,应用超声波辅助法提取杜仲籽油.在单因素试验的基础上,通过正交试验确定了超声波辅助提取杜仲籽油的较佳工艺条件.结果表明,杜仲籽油的较佳提取工艺条件为料液比12ml/g,提取温度50℃,提取时间15min,超声波功率225W,在该条件下杜仲籽油得率27.24%.     

新疆油田稠油开发固体废物对环境的影响及处置措施

新疆油田九1～九5区稠油开发过程中,产生了大量的固体废物,主要包括落地原油、废钻井液和岩屑及原油处理站的含油泥砂,如果处理不当,会对环境造成极大的危害。通过对各主要污染物的环境影响分析,提出了几种针对性的防治措施,以确保油田开发实现清洁生产,达到经济效益、环境效益和社会效益统一。     

实施西部开发战略应注意资源开发区的环境保护问题

实施西部开发战略应注意矿产资源开发、土地资源开发、水资源开发、森林资源开发、草地资源开发、农业资源开发、生物资源开发和旅游资源开发等活动的环境保护问题，本文就此问题提出建议。     

堆肥添加剂降低碳氮损失的微生物学机制研究

为了探明添加剂如何影响堆肥微生物优势群落的演替进而影响碳氮损失,以玉米秸秆和鸡粪为原料,添加不同量的生物质炭和凹凸棒作为添加剂,设置5个处理（CK （鸡粪+玉米秸秆）、BC1（鸡粪+玉米秸秆+5%（干重）生物质炭）、BC2（鸡粪+玉米秸秆+10%（干重）生物质炭）、PG1（鸡粪+玉米秸秆+5%（干重）凹凸棒）和PG2（鸡粪+玉米秸秆+10%（干重）凹凸棒））进行堆肥.结果表明,相较于CK,BC1、BC2、PG1、PG2处理的碳和氮损失分别减少了8.60%、12.05%、2.03%、6.14%和14.54%、20.14%、8.40%、11.23%.优势微生物菌群与碳氮损失的冗余分析表明,添加10%生物质炭和添加10%凹凸棒都显著促进了堆肥过程中固氮类细菌相对丰度,而抑制反硝化细菌的相对丰度,且添加10%生物质炭效果更佳;KEGG分析表明,添加10%生物质炭显著影响氨基酸代谢和碳水化合物代谢功能基因,而添加10%凹凸棒显著影响氨基酸代谢功能基因.由此可见,10%添加剂的碳氮损失都低于5%添加剂的处理,添加生物质炭的碳氮损失都低于凹凸棒处理,添加剂通过影响优势微生物群落及其氨基酸代谢和碳水化合物代谢功能基因抑制堆肥过程中的碳氮代谢,从而减少碳氮损失.     

Occurrence,transport, and toxicity of nanomaterials in soil ecosystems: a review

Environmental Chemistry Letters - The recent and widespread use of engineered nanomaterials in many industrial sectors is a rising health issue for living organisms and ecosystems, yet there is...     

Ultrasound-assisted electrodeposition synthesis of nZVI-Pd/AC toward reductive degradation of methylene blue

Environmental Science and Pollution Research - A novel composite (nZVI/Pd-AC) was prepared by loading nanoscale zero-valent iron (nZVI) and Pd on activated carbon (AC) electrode under...     

The pollution halo effect of technology spillover and pollution haven effect of economic growth in agricultural foreign trade: two sides of the same coin?

Environmental Science and Pollution Research - The existing literature on the environmental Kuznets curve (EKC) fails to investigate the spatial attribute of the “pollution halo” effect...