Seasonal and treatment-process variations in invertebrates in drinking water treatment plants

• Seasonal and treatment-process variations in invertebrates in a DWTP were analyzed. • The propagation and leakage of invertebrates in BAC filter were the most serious. • Invertebrates can survive and reproduce in chlorine disinfected clear water tanks. • Proportions of endogenous invertebrates increased along the treatment process. Problems associated with excessive propagation and leakage of invertebrates in drinking water have received increasing attention in recent years. We performed a monthly survey of invertebrate abundance and taxa in the effluent of each treatment stage in a drinking water treatment plant between May 2015 and April 2016 and analyzed seasonal and treatment-process variations in invertebrates. The results showed that invertebrate abundances in raw water, effluent of the biological activated carbon (BAC) filter, and finished water significantly correlated with water temperature, whereas no correlation was observed between water temperature and invertebrate abundance in the effluents of the sedimentation tank and sand filter. The dominant taxa in the effluent of each treatment stage were rotifers, nematodes, and crustaceans. The sedimentation tank could efficiently remove invertebrates with an annual average removal rate of 92%. The propagation and leakage of invertebrates occurred in the sand and BAC filters but more seriously in the latter. The average reproduction rate in the BAC filter was 268.8% with rotifers as the taxon that leaked the most. Invertebrate survival and reproduction were also observed in the chlorine-disinfected clean water reservoir with an average reproduction rate of 41.9%. Owing to differences in chlorine resistance, the reproduction ability of the dominant taxa was in the order nematodes>crustaceans>rotifers. The proportion of endogenous invertebrates gradually increased along the treatment process. The average proportion of endogenous invertebrates in the finished water was higher than 79.0%. Our findings suggested that waterworks should pay more attention to endogenous invertebrate growth.     

基于TROPOMI的扬州市对流层甲醛和二氧化氮时空分布特征分析

以2020年1月—2021年9月对流层观测仪（TROPOMI）卫星观测资料反演获取的对流层甲醛（HCHO）、二氧化氮（NO₂）柱浓度数据为依据,采用统计方法分析了扬州市HCHO和NO₂柱浓度的时空分布特征。结果表明,扬州市对流层HCHO、NO₂平均柱浓度分别为903.01×10¹³, 633.77×10¹³mole/cm²;受太阳紫外辐射影响,HCHO柱浓度变化特征表现为6月最高、1月最低;受气象条件和人为排放强度影响,NO₂则表现为1月最高、8月最低。2021年1—9月扬州市对流层HCHO、NO₂柱浓度月均值同比2020年分别增长4.0%,40.6%。空间分布特征显示,扬州市对流层HCHO和NO₂浓度高值区主要分布在扬州市南部,且浓度高值区域与重点排污企业分布情况较为一致,多为电力供热、工业锅炉、冶金、石化与化工、表面涂层等行业。相关性分析显示,对流层HCHO与气温、臭氧浓度呈显著正相关,而NO₂与气温、臭氧浓度呈显著负相关。     

中国畜禽温室气体排放时空变化及影响因素研究

畜禽业是关系国计民生的重要产业,在满足居民生活物质需求的同时,其生产过程中所伴随的温室气体排放问题已成为不容忽视的环境问题。本文基于LMDI模型系统分析了1991-2013年中国畜禽温室气体排放时空变化及其因素贡献。结果表明:1从时间维度来看,1991-2013年,中国畜禽温室气体排放经历了先快速上升后稳定上升再波动下降的变化特征,总体呈上升趋势。经济效应对畜禽温室气体排放促进作用最大,而强度效应的抑制作用最大,其次是劳动力效应和结构效应。2期间,经济效应促进作用的累计贡献呈指数增长,而强度效应抑制作用的累计贡献呈倒"U",劳动力效应和结构效应抑制作用也不断加强。3从空间维度来看,中国畜禽温室气体排放的区域集中度较高,四川、河南、山东、云南和内蒙古等省(区、市)畜禽温室气体排放一直位居全国前列。4省域各效应作用方向和程度差异显著,四川、青海和云南强度效应抑制作用较大,辽宁、吉林和黑龙江抑制作用较小;山东、四川和黑龙江结构效应抑制作用显著,新疆和青海促进作用明显;四川、河南、内蒙古、山东、云南、湖南和河北经济效应促进作用较大,天津、上海、海南和北京促进作用较小;四川、湖北、江苏和山东劳动力效应抑制作用显著,新疆、黑龙江和内蒙古促进作用明显。最后,基于研究结论,为未来中国畜禽温室气体减排空间发展策略提出了几点建议。     

基于Ward系统聚类的京津冀城市群空气质量时空变化特征与成因分析

京津冀城市群是中国空气污染最严重的区域之一,探明该地区空气质量的时空变化特征和影响因素对空气污染防治具有重要意义.利用2014—2018年空气实时监测数据,运用系统聚类与空间分析方法,研究京津冀城市群空气质量的时空变化特征和关键影响因素,结果表明:2014—2018年京津冀城市群空气质量改善趋势明显,SO2、PM2.5...     

基于ESDA的城市可持续发展能力时空分异格局研究

可持续发展是复杂城市系统的动态变化过程,准确定量地评估和分析城市可持续发展能力,能够为城市发展战略制定、资源优化配置等提供参考依据,具有重要的理论意义和应用价值。本文以2003-2013年间中国30个省级行政区280个地级及以上城市为研究对象,基于数据包络分析(DEA)和探索性空间数据分析(ESDA)方法,研究中国城市可持续发展能力的时空差异特征。首先基于数据包络分析的思路,将资源、环境投入作为输入指标,人口、经济、社会发展作为输出指标,城市每年的发展状况作为评价单元,建立评价指标体系。然后采用探索性空间数据分析方法,分析城市可持续发展能力的时空格局变化,探索其空间分布格局、空间关联模式、空间集聚状态和空间异质特征。结果表明:第一,全国地级以上城市的可持续发展能力上升趋势明显;第二,城市可持续发展能力与经济格局、行政级别存在较好拟合,呈现出东部高于西部、直辖市高于地级市的区域差异特征,地域之间差异正逐步缩小。从空间演变格局来看,2003年、2008年、2013年城市可持续发展能力呈现正的空间自相关,但相关性逐渐减弱;第三,城市可持续发展能力的空间依赖性和空间异质性同时存在,整体热点区主要分布在中国东部地区,而中部、西部地区城市的可持续发展能力逐年提高,并呈局部高值空间聚集状态。     

1990-2015年世界能源时空演变特征研究

能源系统是从能源开采、能源生产到能源运输,再到终端消费或储备全过程的系统工程.能源在区域之间的运输促进了世界能源网络的形成,随着时间推移和各种外部因素的变化,能源空间格局也随着发生剧烈的变化.基于1990-2015年195个国家能源生产消费数据和贸易矩阵,采用双因子趋势图法和社会网络分析法分析世界能源生产、消费与运输的时空演变特征.结果表明:①世界能源的生产主要分布在中东、亚太、前苏联、北美、中南美和西北非,原油、天然气和煤炭的空间格局也存在差异.②世界能源消费增长存在波动,高消费量高增长率的区域分布在亚太和新兴经济体,欧洲能源消费放缓,北美、日本、俄罗斯消费出现负增长趋势.③从世界能源运输来看,能源出口集中在前苏联、中东、西北非和中南美地区,能源进口集中在亚太及欧美地区;世界能源运输整体流动性增强,中东和北非局部时期存在波动;能源生产国外向中心性不断攀升,亚太和新兴经济体内向中心性增长最快;形成“核心-次核心-节点”的层级结构,欧洲地位下降,亚太作用增强,多元化趋势显现;能源运输存在8条主要路径.④经济增长、政治局势、国家关系以及能源开发技术都对世界能源时空格局产生重大影响,各国也纷纷通过能源来源多样化、双多边合作、能源战略储备、新能源开发保证自身能源安全.随着页岩油气开发技术、新能源技术的发展普及,尤其是煤炭消费在世界范围的放缓锐减,未来世界能源空间格局也即将发生重大调整.     

Atmospheric radon in Hong Kong

For the first time in Hong Kong, atmospheric radon concentration was continuously monitored between November 2007 and October 2008. This paper presents the results obtained during the 12-month period. The annual mean atmospheric radon concentration in Hong Kong was found to be 9.3 Bq m⁻³ which was close to the level at neighbouring places like Guangdong and Taiwan. An estimation of the dose arising from atmospheric radon to the Hong Kong population was made. The meteorological effects on the variation of atmospheric radon concentration were discussed. It was found that the origin of the airmass and stability of the local atmosphere played vital roles in the seasonal and diurnal variations respectively, whereas precipitation caused abrupt changes in rainy days. An attempt was also made to find out the contribution of atmospheric radon to the ambient gamma dose rate.     

中国农业碳排放时空特征及影响因素分解

农业生产所导致碳排放大幅增加以及引发的环境问题,越来越受到人们的关注.本研究基于农业生产中6个主要方面的碳源,测算了我国1993-2008年农业碳排放量.发现自1993年以来我国农业碳排放处于阶段性的上升态势,总体上可分为快速增长期、缓慢增长期、增速反弹回升期、增速明显放缓期等四个变化阶段.其中农业碳排放总量和强度年平均增长率分别为4.08％、2.38％.农业碳排放总量较高地区主要集中在农业大省,农业碳排放强度较高地区主要集中在发达城市、东部沿海发达省份和中部农韭大省.进一步通过Kaya恒等式变形对农业碳排放影响因素进行分解研究,结果表明,效率因素、结构因素、劳动力规模因素对碳排放量具有一定的抑制作用,1994-2008年与基期相比分别累计实现12.95％、26.62％、33.29％的碳减排,而农业经济发展则对农业碳排放具有较强推动作用,累计产生154.94％的碳增量.最后,据此提出促进农业减排的政策建议.     

近50多年青海玉树冻土变化特征分析

利用青海玉树县从建站至2009年的冻土观测资料,分析了玉树土壤年最大冻结深度,冻结初、终日,无冻土期变化特征。结果表明：近50多a,玉树县土壤冻结具有明显的季节变化特征,冻结主要出现在10月~翌年4月;6月中旬~9月上旬为无冻土安全期;多年平均无冻土期173 d,80%保证率下的无冻土期为147 d（不足5个月）;玉树土壤年最大冻结深度没有明显的变化趋势,仅呈阶段性变化特征。0~5 cm土壤冻结初、终日没有明显变化趋势,10~30 cm深度土壤冻结初日呈变早、终日呈推迟的趋势。而近50 a玉树冬季平均气温、平均最低气温及年极端最低气温均呈显著上升趋势。由此说明对季节性冻土区的玉树而言,气候变暖并不一定意味着其年最大冻结深度变薄、表层土壤冻结初日推迟、终日提早,土壤冻结深度的变化除与温度有关外可能还受其他要素的影响。该结论与我国部分学者对青藏高原南部冻土研究结论一致     

Seasonal variations of hydroxylated and methoxylated brominated diphenyl ethers in blue mussels from the Baltic Sea

Hydroxylated polybrominated diphenyl ethers (OH-PBDEs) and methoxylated polybrominated diphenyl ethers (MeO-PBDEs) found at high levels in the Baltic biota are mainly natural products, but can also be formed through metabolism or abiotic oxidation of polybrominated diphenyl ethers (PBDEs). The formation of OH-PBDEs is of concern since there is growing evidence of phenolic toxicity. This study investigates seasonal variations in levels of OH-PBDEs and MeO-PBDEs, focusing on an exposed species, the blue mussel (Mytilus edulis), sampled in the Baltic Sea in May, June, August and October of 2008. Both the OH-PBDE and MeO-PBDE levels in the mussels showed seasonal variations from May to October, the highest concentration of each congener appearing in June. The seasonal variation was more marked for OH-PBDEs than in MeO-PBDEs, but all congeners showed the same trends, except 6-MeO-BDE47 and 2′-MeO-BDE68, which did not significantly decline in concentrations after June. Biotic or abiotic debromination is suggested as a possible reason for the rapid decrease in methoxylated penta- and hexa-BDE concentrations observed in blue mussels from June to August, while the tetraBDE concentrations were stable. In addition, 1,3,7/1,3,8-tribrominated dibenzo-p-dioxins showed the same seasonal variation. The seasonal variations indicates natural formation and are unlikely to be due to transformation of anthropogenic precursors. The levels of PBDEs were fairly constant over time and considerably lower than those of the OH-PBDEs and MeO-PBDEs. The timing of the peaks in concentrations suggests that filamentous macro-algae may be important sources of these compounds found in the blue mussels from this Baltic Sea location.