Magnetic chitosan/sodium alginate gel bead as a novel composite adsorbent for Cu(II) removal from aqueous solution

Environmental Geochemistry and Health - Using sodium alginate hydrogel as skeleton, in combination with chitosan and magnetic Fe3O4, a new type of magnetic chitosan/sodium alginate gel bead (MCSB)...     

北京2013年1月连续强霾过程的污染特征及成因分析

以北京市2013年1月份连续灰霾天气中10~16日的强霾污染过程为例,利用MPL-4B型IDS系列微脉冲激光雷达观测资料由Fernald算法反演得到此次污染过程中气溶胶垂直分布特性,结合地面气象条件和天气形势分析污染原因,并讨论与气溶胶地面监测数据的符合性.结果表明:此次连续强霾过程污染严重,观测时段内89.4%的时间出现霾,39.8%的污染时段达到重度霾级别,其中大气地表消光系数与PM2.5浓度变化呈显著线性相关关系,相关系数达0.95.研究过程内,大气边界层在91%的时段低于500m,平均仅为293m,低边界层抑制了污染物的有效扩散;近地面垂向各高度的消光系数持续达到1.5km-1以上,对比气溶胶退偏比发现城市上空的大气强消光为气溶胶颗粒物和大气水分共同导致;气溶胶光学厚度(AOD,532nm)较大,有83.6%的时段超过1,且受相对湿度影响较大,相对湿度偏小时段的AOD值主要为气溶胶颗粒贡献,相对湿度较大时段,细颗粒物吸湿增长导致AOD受大气水分干扰显著.连续静稳的天气形势和区域污染是导致此次强霾发生和持续的主要原因,高湿天气则加剧了灰霾状况.     

Ambient sulfur dioxide,nitrogen dioxide,and ammonia at ten background and rural sites in China during 2007–2008

We present two years (January 2007–December 2008) of atmospheric SO₂, NO₂ and NH₃ measurements from ten background or rural sites in nine provinces in China. The measurements were made on a monthly basis using passive samplers under careful quality control. The results show large geographical and seasonal variations in the concentrations of these gases. The mean SO₂ concentration varied from 0.7 ± 0.4 ppb at Waliguan on Qinghai Plateau to 67.3 ± 31.1 ppb at Kaili in Guizhou province. The mean NO₂ concentration ranged from 0.6 ± 0.4 ppb at Waliguan to 23.9 ± 6.9 ppb at Houma in southern Shanxi. The mean NH₃ concentration ranged from 2.8 ± 3.0 ppb at Shangdianzi in northeastern Beijing to 13.7 ± 8.4 ppb at Houma. At most sites, SO₂ and NO₂ peaked in winter and reached minima in summer, while NH₃ showed maximum values in summer and lower values in cold seasons. On the whole, the geographical distributions of the observed gas concentrations are consistent with those of emissions. The ground measurements of SO₂ and NO₂ are contrasted to the SCIAMACHY SO₂ and OMI NO₂ tropospheric columns, respectively. Although the satellite data can capture the main features of emissions and concentrations of SO₂, they do not reflect the variations of SO₂ in the surface layer. The situation is better for the case of NO₂. The OMI NO₂ columns capture the geographical differences in the ground NO₂ and correlate fairly well with the ground levels of NO₂ at six of the ten sites.