雷州无瓣海桑群落7种元素的生物累积和循环

在雷州市附城镇岚北人工生态恢复的 7a生无瓣海桑群落生物量调查的基础上 ,对所采集的无瓣海桑进行了植物体各组分样品的灰分和元素含量测定与循环分析 ,结果表明 :无瓣海桑植物体不同组分的灰分含量范围为 2 .2 7%～ 2 6 .4 1% ,以细根的含量最高 ,枯枝的含量最低 .植物体各组分中 7种元素质量分数范围分别为K 0 .11%～ 1.5 6 % ,Na0 .11%～ 1.6 6 % ,Ca 0 .2 0 %～ 2 .6 6 % ,Mg 0 .15 %～ 1.5 9% ,Fe 0 .0 4× 10 -3 ～ 9.6 4× 10 -3 ,Zn 0 .0 5× 10 -4～ 1.0 3× 10 -4,Cu0 .16× 10 -5～ 1.5 0× 10 -5.其加权平均的富集系数为 0 .0 5～ 9.70 ,其中Ca >K >Cu >Na >Mg>Zn >Fe .群落现存生物量中的累积储量分别为K 10 9.76gm-2 ,Ca 138.89gm-2 ,Na 86 .5 7gm-2 ,Mg 81.0 7gm-2 ,Fe 13.139gm-2 ,Zn 0 .4 83gm-2 ,Cu 0 .10 8gm-2 .群落 2 0 0 1年的元素存留累积储量分别为Ca4 1.6 8gm-2 ,K 37.2 4gm-2 ,Mg 2 7.33gm-2 ,Na2 5 .5 6gm-2 ,Fe 4 .2 75gm-2 ,Zn 0 .188gm-2 ,Cu 0 .0 39gm-2 .2 0 0 1年归还量分别为Ca 2 8.5 9gm-2 ,K 16 .83gm-2 ,Mg 12 .0 7gm-2 ,Na 11.5 8gm-2 ,Fe 0 .916gm-2 ,Zn 0 .14 1gm-2 ,Cu 0 .0 2 6gm-2 .年吸收量分别为Ca 70 .2 7gm-2 ,K 5 4 .0 7gm-2 ,Mg 39.4 0gm-2 ,Na 37.1     

柳州地区各种红壤土种的酸沉降临界负荷研究

应用简单质量平衡法，多层模型ＰＲＯＦＩＬＥ和基于植物响应标准计算柳州红壤和土种的酸沉降临界负荷，并建立了系统完整地收集，测量与估算模型所需参数的方法。结果表明，柳州红壤各土种的硫沉降临界负荷为０．５０－１．８０ｋｅｑ．ｈｍ＾－２．ａ＾－１，为保护９５％的土壤不受酸沉降危害，柳州土壤的潜在酸度，酸度和硫沉降临界负荷分别为１．８ｋｅｑ；ｈｍ＾－２．ａ＾－１，１．９ｋｅｑ．ｈｍ＾－２．ａ＾－１和０．７０     

岷江水系河水与沉积物中稀土,稀有元素背景值及其特征初探

报告了岷江水系河水及沉积物中８种稀土元素（Ｌａ，Ｃｅ，Ｎｄ，Ｓｍ，Ｅｕ，Ｔｂ，Ｙｂ，Ｌｕ）及８种稀有元素（Ｒｂ，Ｃｓ，Ｓｒ，Ｂａ，Ｓｂ，Ｔｈ，Ｓｃ，Ｕ）的背景值及其特征，并对元素的排列顺序及元素间的相关关系进行了初步探索，还列出了１６种元素在原水同积物中的相关矩阵及相互间的相关回归方程。     

长江口和黄河口沉积物非残渣态中元素的相关性

研究了长江口、黄河口表层沉积物中元素可提高取量间的相关性、元素可提取量与粒度组成之间的关系。通过对两个区域不同类型的大量沉积物的研究结果表明：用１ｍｏｌ／ＬＨＣｌ或０．５ｍｏｌ／ＬＨＣｌ＋Ｈ２Ｏ２提取沉积物，元素Ｃｕ、Ｚｎ、Ｐｂ、Ｃｏ、Ｌｉ、Ｎｉ、Ｆｅ、Ｋ、Ａｌ的提取量之间存在显著的正相关关系；元素Ｚｎ、Ｃｕ、Ｐｂ、Ｃｏ、Ｌｉ、Ｎｉ、Ｆｅ、Ｋ、Ａｌ的可提取量与沉积物中粘土含量呈显著的正相关关系；与     

昆明红壤环境下酸沉降对二种树木生长的影响

将昆明红壤人工酸化后进行树木生长实验。发现昆明红壤的酸缓冲能力非常大。在 12 0meqH /Lsoil的酸添加处理区也没有发现树木生长的显著下降。根据实际情况判断 ,认为没有必要继续加大酸添加强度进行实验     

微波消解、ICP-AES法快速测定水底底泥中的微量元素

采用微波消解样品,电感耦合等离子体发射光谱法(ICP-AES),在射频功率:1.1KW,等离子气流量:15.0L/min,辅助气流量:1.50L/min,雾化气流量:0.5 L/min,蠕动泵转速20r./min下,快速测定底泥中微量元素Cu、Pb、Zn、Cr、Cd、Ni、Mn含量的方法,方法快速简便、准确度高、精密度好,可用于各类底泥中微量元素的测定.     

汽车排气净化催化剂三效性能的研究

本文对Ky系列催化剂处理汽车排气中CO,HC和NO_x的三效性能进行了研究,用CVS法测定排放污染物的重量和转化效率;通过行车60 000km,证明高温老化引起催化剂表面结构的改变,是导致催化剂活性下降的主要原因,新改进的催化剂有较好的热稳定性和三效性能。     

Company engagement with supply chains to protect biodiversity and rare,threatened, and endangered species

Future global megatrends project a population increase of 2 billion people between 2019 and 2050 and at least 1–2 billion people added to the global middle class between 2016 and 2030. In addition, 68% of the world's population is projected to be living in urban areas by 2050. With these projected large population increases and shifts, demand for food, water, and energy is projected to grow by approximately 35, 40, and 50%, respectively, between 2010 and 2030. In addition, between 1970 and 2014 there was an estimated 60% reduction in the number of wildlife in the world and an estimated net loss of 2.9 billion birds, or 29%, in North America between 1970 and 2018. Loss of species populations and number of species is interconnected with reduced health of biodiversity and ecosystems. Human activity has been the main catalyst for these substantial declines primarily through impacts on habitats. These losses are accelerating. Since a company's supply chain environmental impacts are often as great or greater than its own direct environmental impacts, it may be prudent for companies to engage with their supply chains to protect and enhance habitats and biodiversity and protect rare, threatened, and endangered species. As one example, companies may have opportunities and strategic reasons to include requirements in their supplier codes of conduct and supplier standards for suppliers to protect biodiversity and rare, threatened, and endangered species, as well as additional requirements to expand or enhance habitats and ecosystems to increase biodiversity. This article follows one pathway that companies could pursue further and with greater speed—to engage with their supply chains to strengthen supplier codes of conduct to protect biodiversity and rare, threatened, and endangered species. The importance of forests, private land, and landscape partnerships is discussed as means to protect much more of the planet's biodiversity and rare, threatened, and endangered species. Lastly, the article identifies examples of opportunities for companies to more formally incorporate biodiversity into their business, supply chain, and sustainability strategies.     

Emission control strategies of hazardous trace elements from coal-fired power plants in China

China's energy dependents on coal due to the abundance and low cost of coal. Coal provides a secure and stable energy source in China. Over-dependence on coal results in the emission of Hazardous Trace Elements (HTEs) including selenium (Se), mercury (Hg), lead (Pb), arsenic (As), etc., from Coal-Fired Power Plants (CFPPs), which are the major toxic air pollutants causing widespread concern. For this reason, it is essential to provide a succinct analysis of the main HTEs emission control techniques while concurrently identifying the research prospects framework and specifying future research directions. The study herein reviews various techniques applied in China for the selected HTEs emission control, including the technical, institutional, policy, and regulatory aspects. The specific areas covered in this study include health effects, future coal production and consumption, the current situation of HTEs in Chinese coal, the chemistry of selected HTEs, control techniques, policies, and action plans safeguarding the emission control. The review emphasizes the fact that China must establish and promote efficient and clean ways to utilize coal in order to realize sustainable development. The principal conclusion is that cleaning coal technologies and fuel substitution should be great potential HTEs control technologies in China. Future research should focus on the simultaneous removal of HTEs, PM, SOx, and NOx in the complex flue gas.     

2017—2018年秋冬季唐山市PM2.5中元素组成特征及来源解析

为研究唐山市大气PM_2.5中元素组成特征及其来源,于2017年10月19日—2018年1月31日（秋冬季）在唐山市的超级站（典型城市站点）、开平站（工业站点）和古冶站（工业站点）开展了PM_2.5的手工连续采样,定量分析测定了PM_2.5中23种无机元素.结果表明:Si、Al、Ca和Na等地壳元素的质量浓度均在10月最高,在1月最低.10月,ρ（Cr）在开平站最高（0.020 0 μg/m3）,随后逐月略微降低,其主要受钢铁冶炼工业的减产和限产影响.多数重金属元素质量浓度在11月或12月最高,包括Zn、Pb、Mn、Cu、Ni、Se、V、Cd和Co,其可能受燃煤取暖影响.Cd、Zn、Pb和Cu四种元素的富集因子值分别为2 677、616、422和77,均达到极强富集,且均受人为排放源影响最大.基于因子分析法得出,唐山市大气PM_2.5中元素的主要来源有燃煤源、钢铁工业源与扬尘源的混合源、交通源以及土壤扬尘源,其方差贡献率分别为56.3%、21.6%、7.1%、5.4%.研究显示,秋冬季唐山市大气颗粒物PM_2.5中元素最主要的污染来源为工业源、燃煤源和扬尘源.