SUSTAINABILITY AT THE LOCAL LEVEL: MANAGEMENT TOOLS AND MUNICIPAL TAX INCENTIVE MODEL

The implementation of sustainable development may seem a simple concept when written on paper. However to carry-out long term actions put forward by the Agenda 21 (AG21) at the local level represents one of the main challenges as municipal governments in general do not have the capacity to effectively implement the process. Regional environmental assessment (REA) has shown to be effective in supporting decision-making not only to correct environmental problems due to past unsustainable social-economic developments but also help local governments to implement sustainable actions. However this requires long-term investments of AG21 plans and projects. The allocation of regular and consistent financial resources is one of the main ingredients for the sustainable development process. But traditional plans and projects financed by national and/or international funds may not be sustainable in the long-term because they become dependent on external funding. Research demonstrate that innovative economic instruments such as ecotaxes represent a feasible alternative to sponsor local sustainability because taxes are collected permanently by the government and could be invested in continuous actions. Ecotaxes experiences have provided important reference to structure a municipal incentive model (MIM) to sponsor AG21’s environmental plans and projects on a long-term (permanent) basis. However sustainable development cannot be solely through economic investments. A comprehensive municipal environmental management scheme (MEMS) has been established to support the incentive model. The scheme seeks not only to improve local institutional framework but also incentive continuous participation of local stakeholders at all levels of society. Participatory events and the provision of incentives (educational and financial) are key to motivate society to protect the environment and support actively the sustainable development process as emphasised in the RIO-92 Conference.     

A Marine Pollution Study of Northeast Coastal Water Off Taiwan Island

The coastal water of northeast Taiwan island, called 'Yin-Yang Hai' for its distinct yellow colour compared with blue offshore water, was investigated from 1989 to 1990 by the authors. Biological study showed the dominant species of plankton to be Copepoda, Cladocera, planktonic eggs and Diatoma. Dominant species of benthos were young crabs, Amphipoda and Annelida, with Amphipoda usually occurring in heavily polluted areas. Heavy metal data showed that the concentration of copper was high. the copper and iron concentration in algae of the intertidal zone was also high. the concentrations of iron and copper in inshore water were also higher than in offshore water. By comparison of the pH and salinity distribution of this area, we conclude that this coastal water has been polluted by acid waste water from coastal industry. the suspended solids concentration in sea water is high. Flocculation occurring at the boundary of fresh and saline water might be a reason for the distinct yellow colour of the water of this area. Further study is required.     

Effects of high temperature on larval development and metamorphosis of Arachnoides placenta (Echinodermata: Echinoidea)

Adults of the sea urchin Arachnoides placenta (L.) were induced to spawn, and eggs were fertilized at 28°C in September 1989. After 5 min, eggs were transferred to 28, 31, 34, or 37°C and reared to metamorphosis. Embryos were observed at 20-min intervals during the first 2 h; larvae were observed daily. The cleavage was higher at higher temperatures. Embryos reared at 28°C were still at the 4th cleavage (16-cell stage) after 100 min, while those at 34°C had reached the 5th cleavage (32-cell stage). All embryos reared at 37°C died on the second day. Incidence of abnormality was 20 to 30% at 28 and 31°C, 48% at 34°C, and 77% at 37°C. The 8-arm stage was reached after 4 d at 28°C, 3 d at 31°C and 2 d at 34°C. Larvae displayed decreasing body length and arm length with increasing temperature. Larvae at 31°C have relatively long arms, as a result of a decrease in body length, not because of increased arm length. Incidence of metamorphosis was 43.9±1.7% (mean/plusmn;SD) at 28°C, 24.5±1.9% at 31°C, and 5.3% at 34°C. The size of metamorphosed juveniles was significantly larger at 28°C than at 31 and 34°C. Temperatures of 31°C negatively affect larvae and juveniles of the sand dollar.     

基于不同废污泥源的短程反硝化快速启动及稳定性

为探究不同废污泥源快速启动短程反硝化和实现稳定NO_2~--N积累的可行性,在3个完全相同的SBR反应器(S1、S2和S3)分别接种:实验室城市污水反硝化除磷系统排泥、城市污水厂剩余污泥及河涌底泥,比较其短程反硝化启动快慢和NO_2~--N积累特性,考察系统短程反硝化活性和NO_3~--N→NO_2~--N转化性能,并从微生物学角度分析反应器功能菌群特征.结果表明,在乙酸钠为唯一碳源、高碱度和适宜COD/NO_3~--N比进水条件下,3个SBR短程反硝化反应器在短时间内均能够成功启动,系统平均NO_3~--N→NO_2~--N转化率为S1 S2 S3(75. 92% 73. 36% 69. 90%).同时发现持续低温条件下S1和S2呈现不同程度的短程反硝化性能恶化趋势,但S3能够稳定维持良好NO_2~--N积累性能.微生物高通量测序表明,变形菌门和拟杆菌门居PD系统主导地位,3个短程反硝化反应器NO_2~--N积累关键功能菌属Thauera属丰度差异明显:S3 S1 S2(25. 09% 4. 71% 3. 60%),表明S3具备稳定高效的NO_2~--N积累性能,同时高丰度Thauera属可能是维持低温短程反硝化活性的重要原因.     

典型西南工业城市柳州市核心区大气污染物时空分布与气象因素研究

为研究柳州市核心区大气污染物浓度时空变化规律与气象因素之间的关系,统计分析了2018年全年研究区内6个自动监测站点PM_(2.5)、PM_(10)、SO_2、NO_2、O_3和CO的浓度监测数据和气象站气象数据,并对28次超标日污染物来源进行了解析.结果显示:①核心区颗粒污染物污染较为严重,且以PM_(2.5)为主的细颗粒污染物仍为柳州市主要的大气污染物;各污染物月均浓度季节差异显著,除NO_2外柳州大气污染物浓度下降明显,指示柳州市多项节能减排综合整治措施成效显著;PM_(2.5)、PM_(10)、CO受早晚高峰期影响,浓度日变化均呈双峰型;NO_2在不同季节峰型不同,作为O_3前体物其浓度日变化与O_3相反,呈现"早峰午谷"的变化趋势.②通过对污染物浓度插值发现,由于核心区主要工商业区位于西部且处于主导风向下风向,故PM_(2.5)和SO_2浓度西北高、东南低,PM_(10)、NO_2和CO浓度西南高、东北低;核心区东部的山区为O_3生成带来大量前体物,使O_3浓度东南高、西北低.③由于气候特征,核心区春、夏季主要气象因素均为降水量;秋季的主要气象因素是风速,风速与污染物的负相关关系表明了风的扩散效应;冬季大部分污染物与气象因素的相关性不显著,表明人为因素对污染物的影响大于气象因素;核心区大气污染物主要来源于局地排放和区域传输,且南北主导风向对大气污染影响最大.④HYSPLIT模型结果指示柳州超标日大气污染物主要来自于珠三角地区,且陆源颗粒物浓度普遍比海洋源高,来自南部的远距离输送气流颗粒物含量最低,表明远距离输送为影响颗粒物传播的主要原因.     

哈尔滨市秸秆焚烧大气污染负荷估算方法研究

本文针对近些年哈尔滨秋末冬初大气污染程度增加的溯源问题,基于静风污染气象及降雪对秸秆焚烧的影响等基本假设,采用箱式模型和优化拟合的方法对秸秆焚烧产生污染物的源强及其负荷进行了估算.通过对2015年和2017年典型时段数据的优化拟合得到降雪前重污染天气下PM₁₀排放源强分别为20.16、21.83 μg·m^-2·s^-1,CO的排放源强分别为149.32、138.65 mg·m^-2·s^-1;降雪后重污染天气下PM₁₀排放源强分别为15.98、7.09 μg·m^-2·s^-1,CO的排放源强分别为122.91、89.21 mg·m^-2·s^-1.由降雪前后各污染物的源强差得到2015年和2017年秸秆焚烧产生的PM₁₀的排放源强分别为4.18、14.74 μg·m^-2·s^-1,负荷分别为20.73%、67.52%;CO的排放源强分别为26.41、49.44 mg·m^-2·s^-1,负荷分别为17.69%、35.66%.本文为相关清单的研究提供了一种客观的校核方法,具有重要的社会、环境及现实意义.