青岛市建设循环型经济社会的探讨

以青岛市为例,通过对传统型经济社会发展所面临环境问题的对比分析,阐述了发展循环经济、建设循环型经济社会对我国经济社会可持续发展的重要意义。指出为了实现2008年“绿色奥运”和生态型城市的建设目标,在青岛市发展循环经济,建立循环型经济社会的可能性和必要性。提出了青岛市发展循环经济、建设循环型经济社会的实施对策。     

城市扩展过程对湿地影响的情景模拟研究——以河北怀来为例

在复杂多变的环境下,情景模拟法因其能考虑突发干扰的影响并能聚焦长期规划而表现出突出的优势。怀来是北京重要的水源地和环境保护屏障,2022年北京-张家口冬奥会的筹办将可能加快怀来的经济发展和城市扩展,进而对湿地的空间压力产生重要影响。因此,论文利用情景模拟法,结合城市扩展模型（land use scenario dynamics-urban,LUSD-urban）和湿地空间压力模型,模拟了趋势外推、城市规划和冬奥会3种情景下怀来未来城市扩展对湿地的空间压力。结果显示城市扩展导致怀来湿地空间压力增大,湿地平均压力从2000年的0.399增加到2013年的0.439,增长了10.03%。同时,湿地空间压力高于0.5的像元比例从6.73%增加到17.42%。3种情景下,2013—2030年怀来的湿地空间压力将增长0.002~0.005。冬奥会的举办将为怀来湿地带来更大的空间压力,冬奥会情景下湿地压力的热点区面积最大,为83.74 km²,是3种情景下共有热点区面积的1.44倍,新保安镇、土木镇和沙城镇的非城市用地面临的空间压力较大。因此,怀来县在未来制定城市规划时应充分考虑县内湿地生态系统,在保护湿地资源的基础上有效促进经济的发展。     

冬奥会期间京津冀及周边区域空气质量时空特征、气象影响和减排效果评估

对比分析2015～2022年冬奥会期间(1月31日至2月20日)京津冀及周边区域44城市空气质量时空演变特征,量化同期气象、协同减排和跨区域传输对PM_2.5浓度及组分变化贡献,为不利气象条件下区域空气质量联防联控提供科学参考.结果表明,2022年44城市PM_2.5浓度为近8年农历同期最低(46μg·m^-3),优良天占比最高(83.3%),不存在重污染天.PM_2.5污染南重北轻,高值区主要集中在太行山沿线及燕山传输通道城市.2016年在春节中期未管控烟花爆竹燃放等源排放强度下,优良天占比93.5%,大气强扩散能力对空气质量改善至关重要.2022年静稳天气指数(SWI)同比增加2.1,大气扩散能力转差,44城市ρ(PM_2.5)均值和峰值同比下降14μg·m^-3和76μg·m^-3,北京减排对PM_2.5浓度降幅较未采取前增大96%,晋鲁豫地区在气象造成PM_2.5浓度上升的不利背景下,峰值下降87μg...     

北京市典型道路交通环境细颗粒物元素组成及分布特征

对北京市典型道路交通环境中不同粒径段（0.2～0.5μm、0.5～1.0μm和1.0～2.5μm）的细颗粒物进行了采样分析,在2008—2009年期间5个阶段内共采集了198个细颗粒物样品.通过XRF分析得到细颗粒物中Al、Na、Mg、K、Ca、Si、S、Cl、Fe、Mn、Ti、Cu、Zn、As、Br和Pb16种元素的质量浓度.含量较高的元素有S、K、Fe、Cl、Si、Ca和Zn,占测试元素总浓度的90%以上.应用富集因子法将元素分为地壳元素、双重元素和污染元素三类.应用因子分析法分离出两个主要因子,因子1主要与地壳元素和双重元素相关,可归于扬尘源的贡献;因子2主要与污染元素相关,可能来自机动车、燃煤、生物质燃烧和工业等排放源.人为源对小粒径（0.2～0.5μm）颗粒物的贡献较大,而地壳源的贡献更集中于大粒径段（1.0～2.5μm）.多数地壳元素和双重元素在夏季和冬季均随粒径的增大而富集,且冬季浓度较高,而多数污染元素的分布形态存在季节差异.Br、As和Pb夏季在0.5～1.0μm出现峰值,而冬季在0.2～0.5μm出现峰值.冬季因采暖增加的煤和生物质的燃烧造成部分元素浓度在0.2～0.5μm有显著增加.云层内部的硫酸盐生成过程可能是夏季S元素在0.5～1.0μm出现峰值的原因.通过奥运时期与非奥运时期元素浓度和分布的比较,发现奥运时期交通源临时控制措施对机动车排放和道路扬尘均有显著的削减作用,削减率分别为53%和63%,且随粒径增大而增加.     

北京开展整体"安全奥运"建设的思考

从城市现代化的国际背景及安全态势入手。结合北京城市的灾害背景,系统研究并提出了2008年“安全奥运”建设应强调全过程、全寿命周期的控制对策,并解析了“安全奥运”的风险、工程、管理与文化的四大基本思路。     

Evaluating the air quality impacts of the 2008 Beijing Olympic Games: On-road emission factors and black carbon profiles

The aggressive traffic interventions and emission control measures implemented to improve air quality during the 2008 Beijing Olympic Games created a valuable case study to evaluate the effectiveness of these measures on mitigating air pollution and protecting public health. In this paper, we report the results from our field campaign in summer 2008 on the on-road emission factors of carbon monoxide, black carbon (BC) and ultrafine particles (UFP) as well as the ambient BC concentrations. The fleet average emission factors for light-duty gasoline vehicles (LDGV) showed considerable reduction in the Olympic year (2008) compared to the pre-Olympic year (2007). Our measurement of Black Carbon (BC), a primary pollutant, at different elevations at the ambient site suggests consistent decrease in BC concentrations as the height increased near the ground level, which indicates that the nearby ground level sources, probably dominated by traffic, contributed to a large portion of BC concentrations in the lower atmospheric layer in Beijing during summertime. These observations indicate that people living in near ground levels experience higher exposures than those living in higher floors in Beijing. The BC diurnal patterns on days when traffic control were in place during the Olympic Games were compared to those on non-traffic-control days in both 2007 and in 2008. These patterns strongly suggest that diesel trucks are a major source of summertime BC in Beijing. The median BC concentration on Olympic days was 3.7 μg m⁻³, which was dramatically lower than the value on non-traffic-control days, indicating the effectiveness of traffic control regulations in BC reduction in Beijing.     

中国典型冰雪旅游地开发模式及优化路径

北京冬奥会的筹办为中国冰雪旅游发展带来巨大契机,促进了冰雪旅游地的蓬勃发展。基于冰雪旅游地系统理论,构建了冰雪旅游地发展水平评价指标体系,并利用层次分析法、熵权法及加权Topsis法,对崇礼、亚布力、神农架、西岭雪山四个中国典型冰雪旅游地发展水平进行了测度。结果表明：崇礼冰雪旅游发展水平最高,亚布力次之,神农架及西岭雪山仍有待提升。基于此,提炼出四种典型冰雪旅游地开发模式,包括资源主导内驱模式、市场主导外驱模式、资源市场双核共驱模式以及资源市场政策综合齐驱模式。同时,从冰雪旅游地系统视角,提出了中国冰雪旅游地开发优化路径。研究有助于丰富冰雪旅游开发相关理论,为中国冰雪旅游地高质量发展提供智力支撑和案例借鉴。     

青岛市前海一线海域水质评价与水质改善措施研究

系统调查了青岛市前海一线水质状况,采用单因子污染指数、富营齐化指数、有机评价指数法进行了水质评价.对污染成因进行了分析,提出了进一步改善海域水质的对策建议.     

南京青奥会空气质量保障联合观测分析研究

2014年8月,为做好南京青奥会空气质量保障工作,江苏省环境监测中心联合中科院大气物理所、南京大学等36家单位,开展了为期一个月的空气质量保障联合观测,共获取监测数据5万多个,巡航观测里程超9 000 km,编制预报及分析报告87份,空气质量预报准确率达80%。结果表明,强力管控措施的实施,对缓解空气污染效果显著;通过联合团队观测方式,集中了产、学、研、用的技术优势和科研力量,带动了全省空气质量监测与分析能力的整体提升,为青奥会空气质量保障工作提供了强有力的技术支撑。     

Local and regional contributions to PM2.5 in the Beijing 2022 Winter Olympics infrastructure areas during haze episodes

• Regional transportation contributed more than local emissions during haze episodes. • Short-range regional transportation contributed the most to the PM_2.5 in the OIAs. • Low wind speeds and low PBLHs led to higher local contributions to Beijing. The 2022 Winter Olympics is scheduled to take place in Beijing and Zhangjiakou, which were defined as OIAs (Olympic infrastructure areas) in this study. This study presents the characteristics and source apportionment of PM_2.5 in the OIAs, China. The entire region of mainland China, except for the OIAs, was divided into 9 source regions, including four regions in the BTH(Beijing-Tianjin-Hebei) region, the four provinces surrounding the BTH and the remaining areas. Using CAMx/PSAT, the contributions of the nine regions to the PM_2.5 concentration in the OIAs were simulated spatially and temporally. The simulated source apportionment results showed that the contribution of regional transportation was 48.78%, and when PM_2.5 concentration was larger than 75 μg/m³ central Hebei was the largest contributor with a contribution of 19.18%, followed by Tianjin, northern Hebei, Shanxi, Inner Mongolia, Shandong, southern Hebei, Henan and Liaoning. Furthermore, the contribution from neighboring regions of the OIAs was 47.12%, which was nearly twice that of long-range transportation. Haze episodes were analyzed, and the results presented the importance of regional transportation during severe PM_2.5 pollution periods. It was also found that they were associated with differences in pollution sources between Zhangjiakou and Beijing. Regional transportation was the main factor affecting PM_2.5 pollution in Zhangjiakou due to its low local emissions. Stagnant weather with a low planetary boundary layer height and a low wind velocity prevented the local emitted pollutants in Beijing from being transported outside, and as a result, local emissions constituted a larger contribution in Beijing.