Will polycentric cities cause more CO2 emissions? A case study of 232 Chinese cities

From 2000 to 2010 China experienced rapid economic development and urbanization. Many cities in economically developed areas have developed from a single-center status to polycentricity. In this study, we used exploratory spatial data analysis (ESDA) to identify the population centers, which identified 232 cities in China as having urban centers. COMP was used to represent urban agglomeration, and POLYD (representing how far is the city's sub-centers to the main center), POLYC (representing the number of a city's centers), and POLYP (representing the population distributed between the main center and the sub-centers) were used to indicate urban polycentricity. Night light data were used to determine the CO₂ emissions from various cities in China. A mixed model was used to study the impact of urban aggregation and polycentric data on the CO₂ emission efficiency in 2000 and 2010. The study found that cities with higher compactness were distributed in coastal areas, and the cities with higher multicentricity were distributed in the Yangtze River Delta and Shandong Province. The more compact the city was, the less conducive it was to improving CO₂ emission efficiency. Polycentric development of the city was conducive to improving the CO₂ emission efficiency, but the number of urban centers had no significant relationship with the CO₂ emission efficiency. Our research showed that the compactness and multicentricity of the city had an impact on the CO₂ emission efficiency and provided some planning suggestions for the low carbon development of the city.     

Ozone pollution characteristics and sensitivity analysis using an observation-based model in Nanjing, Yangtze River Delta Region of China

Ground-level ozone (O₃) has become a critical pollutant impeding air quality improvement in Yangtze River Delta region of China. In this study, we present O₃ pollution characteristics based on one-year online measurements during 2016 at an urban site in Nanjing, Jiangsu Province. Then, the sensitivity of O₃ to its precursors during 2 O₃ pollution episodes in August was analyzed using a box model based on observation (OBM). The relative incremental reactivity (RIR) of hydrocarbons was larger than other precursors, suggesting that hydrocarbons played the dominant role in O₃ formation. The RIR values for NO_X ranged from –0.41%/% to 0.19%/%. The O₃ sensitivity was also analyzed based on relationship of simulated O₃ production rates with reductions of VOC and NO_X derived from scenario analyses. Simulation results illustrate that O₃ formation was between VOCs-limited and transition regime. Xylenes and light alkenes were found to be key species in O₃ formation according to RIR values, and their sources were determined using the Positive Matrix Factorization (PMF) model. Paints and solvent use was the largest contributor to xylenes (54%), while petrochemical industry was the most important source to propene (82%). Discussions on VOCs and NO_X reduction schemes suggest that the 5% O₃ control goal can be achieved by reducing VOCs by 20%. To obtain 10% O₃ control goal, VOCs need to be reduced by 30% with VOCs/NO_X larger than 3:1.     

底泥原位洗脱过程中氮磷含量与形态变化特征

随着城市化进程的不断推进,城市河流底泥中内源氮磷污染问题日益突出.为研究原位洗脱技术对污染底泥中氮、磷物质和成分的作用效果,以北京市凉水河作为研究对象,分别比较了现场试验洗脱与对照组0~30 cm分层底泥以及实验室模拟洗脱处理前后0~10 cm底泥中pH、E_h（氧化还原电位）、容重、含水率、OM（有机质）、TN、TP和氮、磷形态分布的变化特征.结果表明:①现场洗脱对0~5 cm厚度底泥的处理和模拟洗脱处理均对底泥中pH、E_h、含水率的改变以及其中TN、TP的去除效果表现显著,其中,现场试验洗脱组0~5 cm范围底泥中w（TN）、w（TP）分别较对照组降低了66.4%±17.4%、40.8%±24.4%,模拟洗脱处理对底泥中OM、TN、TP的去除率分别达70.1%±4.8%、66.8%±2.0%、43.1%±3.1%.②原位洗脱技术对底泥中TN的去除主要通过对PON（颗粒态有机氮）的去除来实现,现场和模拟试验过程中PON对TN去除的贡献率分别达55.0%和73.6%.③原位洗脱对底泥中TP的去除主要通过对Al-P（铝结合态磷）、OP（有机磷）的去除来实现,现场和模拟试验中Al-P、OP对TP去除的贡献率分别达37.0%、66.2%和31.3%、43.7%.研究显示,原位洗脱技术可有效去除城市河流底泥处理层中的氮磷物质,并以有机氮、磷物质的去除为主.      

不同浓度锌处理下水稻幼苗对镉的累积效应

为探究锌（Zn）对水稻镉（Cd）累积的影响及其根表铁膜所发挥的作用,选取Cd高累积型水稻品种中9优547（简称"Z547"）和Cd低累积型水稻品种金优402（简称"J402"）,采用温室水培试验,研究0、2、5、10、15和20 μmol/L等6个Zn浓度下水稻幼苗对Cd的累积效应,以及不同浓度Zn处理对根表铁膜生成量的影响.结果表明:①随着c（Zn）的增加,Z547和J402水稻幼苗生物量均呈先增后减的趋势,分别在c（Zn）为2和10 μmol/L时达到最大值.②Z547和J402水稻幼苗中w（Cd）均呈先降后增的趋势,分别在c（Zn）为5和2 μmol/L时达到最小值;当水稻幼苗中w（Cd）达到最小值时,Z547根和地上部中w（Cd）分别为31.65和11.47 mg/kg,J402根和地上部中w（Cd）分别为22.58和14.36 mg/kg.③不同浓度Zn处理下水稻幼苗各部位中w（Cd）均与根表铁膜中w（Mn）、w（Fe）、w（Fe+Mn）呈显著正相关,高铁膜处理水稻幼苗中w（Cd）显著高于低铁膜处理,表明根表铁膜生成量的增加会促进Cd在水稻幼苗中的累积.研究显示,当c（Zn）较低时,c（Zn）的增加会抑制水稻幼苗对Cd的累积;当c（Zn）较高时,c（Zn）的增加会促进水稻幼苗对Cd的累积,而Zn可通过控制根表铁膜的生成来影响水稻幼苗对Cd的累积.      

基于边介数的省域生态廊道构建方法优化

我国城市建设和生态保护工作均对土地资源有大量需求,二者之间的矛盾在经济优先发展区表现尤为明显.为了有效地改善生态环境,管控土地利用并引导其变化发展,需要建设具备不可替代特征的省域生态廊道.最小累积阻力模型（minimum cumulative resistance,MCR）是识别生态廊道最常用、有效的模型,但在应用于省域尺度时,MCR模型识别的潜在廊道路由存在冗余的问题.因此,通过引入网络科学中的边介数指数（edge-betweenness）对MCR模型进行优化,计算潜在廊道路由的边介数指数值,选取出其中最为重要和简明的结构来连通生态源地,即提取潜在路由中的骨干路由（backbone route）和关键战略点（key strategic point）作为不可替代的结构来指导省域生态廊道建设.将优化后的MCR模型应用于广东省,构建了全长5 493 km的省域生态廊道,其中包含生态源地20处,关键战略点11个,骨干生态廊道29条.骨干路由与关键战略点构成的不可替代省域生态廊道（irreplaceable provincial corridor）能够实现"廊道数量和占地面积最少、连通性基本不变"的目标.研究显示,边介数能够对潜在路由进行优化筛选,识别出维护省域生态安全的关键结构;不可替代生态廊道能够指导省域生态规划和土地空间的发展利用,并为更高水平的生态安全环境提供了演进的基础;同时也为土地资源紧张的地区提供了建设生态廊道的参考与依据.      

Particulate matter exchange between atmosphere and roads surfaces in urban areas

The deposition and the re-suspension of particulate matter (PM) in urban areas are the key processes that contribute not only to stormwater pollution, but also to air pollution. However, investigation of the deposition and the re-suspension of PM is challenging because of the difficulties in distinguishing between the resuspended and the deposited PM. This study created two Bayesian Networks (BN) models to explore the deposition and the re-suspension of PM as well as the important influential factors. The outcomes of BN modelling revealed that deposition and re-suspension of PM10 occurred under both, high-traffic and low-traffic conditions, and the re-suspension of PM2.5 occurred under low-traffic conditions. The deposition of PM10 under low-volume traffic condition is 1.6 times higher than under high-volume traffic condition, which is attributed to the decrease in PM10 caused by relatively higher turbulence under high-volume traffic conditions. PM10 is more easily resuspended from road surfaces compared to PM2.5 as the particles which larger than the thickness of the laminar airflow over the road surface are more easily removed from road surfaces. The increase in wind speed contributes to the increase in PM build-up by transporting particulates from roadside areas to the road surfaces and the airborne PM2.5 and PM10 increases with the increase in relative humidity. The study outcomes provide a step improvement in the understanding of the transfer processes of PM2.5 and PM10 between atmosphere and urban road surfaces, which in turn will contribute to the effective design of mitigation measures for urban stormwater and air pollution.     

保定市大气污染特征和潜在输送源分析

保定市是京津冀地区重要城市之一.为了解保定市大气污染物质量浓度特征和潜在输送源,对保定市国控点2017年1月1日-12月31日PM₁₀、PM_2.5、SO₂、NO₂、O₃、CO等常规大气污染物数据进行分析,并利用TrajStat后向轨迹模型进行区域传输研究.结果表明:①ρ（PM₁₀）、ρ（PM_2.5）、ρ（SO₂）、ρ（NO₂）分别为（138±96）（84±66）（29±23）和（50±24）μg/m3,与2016年相比分别下降5.9%、9.1%、25.5%和13.1%;ρ（CO）较2016年下降了14.0%;ρ（O₃）较2016年增长了25.2%.ρ（PM₁₀）、ρ（PM_2.5）、ρ（NO₂）和ρ（O₃）分别超过GB 3095-2012《环境空气质量标准》二级标准限值的0.97、1.40、0.25和0.34倍,ρ（SO₂）和ρ（CO）未超标.②除ρ（O₃）外,其他污染物质量浓度均呈冬季最高、夏季最低的季节性特征,其中,冬季PM_2.5污染最为严重,春季PM_2.5~10（粗颗粒物）污染严重.③空气质量模型源解析结果显示,保定市ρ（PM_2.5）约60.0%~70.0%来自本地污染源排放.后向轨迹结果表明,在外来区域传输影响中,保定市主要受到西北方向气团（占比为21.7%~60.0%）远距离传输和正南方向气团（占比为34.8%~50.5%）近距离传输的影响.④PSCF（潜在源贡献因子分析法）和CWT（浓度权重轨迹分析法）分析表明,除保定市及周边区县本地污染贡献外,位于太行山东麓沿线西南传输通道的邯郸市、邢台市、石家庄市是影响保定市PM_2.5的主要潜在源区.研究显示,PM_2.5为保定市大气中的主要污染物,并呈冬季高、夏季低的变化特征,其主要来自西北远距离输送和南部近距离传输.      

长三角背景点夏季大气PM2.5中水溶性无机离子污染特征及来源解析

为研究长三角背景点夏季PM_2.5污染特征,于2018年5月30日—8月15日在上海市崇明岛对PM_2.5样品进行昼夜采集,并对其中水溶性无机离子(Cl-、NO₃-、SO₄2-、Na+、NH₄+、K+、Mg2+、Ca2+)进行了分析.运用PSCF(潜在源贡献)方法判别污染物排放源区,并结合PCA(主成分分析)和PMF(正交矩阵因子)源解析探究PM_2.5来源.结果表明:①观测期间崇明岛ρ(PM_2.5)平均值为(33±21)μg/m3,低于GB 3095—2012《环境空气质量标准》一级标准限值(35 μg/m3),但在部分时段存在显著超标现象,ρ(PM_2.5)最高值在120 μg/m3以上.②水溶性无机离子质量浓度平均值为(14±9.3)μg/m3,占PM_2.5的42.4%,其中SNA(SO₄2-、NO₃-、NH₄+三者统称)为主要离子,占水溶性离子总质量浓度的85.7%.③n(NH₄+)/n(SO₄2-)(NH₄+与SO₄2-的摩尔浓度比)显示,清洁期〔ρ(PM_2.5) < 15 μg/m3〕呈贫铵状态,过渡期〔15≤ρ(PM_2.5)≤35 μg/m3〕和污染期〔ρ(PM_2.5)>35 μg/m3〕均呈富铵状态;过渡期SNA主要以NH₄HSO₄和NH₄NO₃形式存在,而污染期则主要以(NH₄)₂SO₄和NH₄NO₃形式存在.④通过对两次典型污染事件进行离子相关性分析和PSCF分析发现,E1污染事件(5月30日—6月8日)为局地生物质燃烧型污染事件,E2污染事件(7月23日—8月1日)为区域传输污染事件.源解析结果进一步表明,两次典型污染事件期间气态污染物的二次转化对PM_2.5的贡献最显著,贡献率分别为62.8%和59.8%;其次是生物质燃烧,其贡献率分别为32.5%和20.1%;E2污染事件期间海盐源对崇明岛PM_2.5贡献率较高(16.6%),远超过E1污染事件期间对PM_2.5的贡献率(2.7%).研究显示,区域输送对崇明岛PM_2.5有显著贡献,二次颗粒物累积是崇明岛PM_2.5超标的主要原因.      

病毒在土壤中的存活时间与传播能力及其影响因素

土壤是病毒在自然界主要的分布场所,也是病毒传播的一种媒介.对流感病毒、肠道病毒、甲型肝炎病毒和冠状病毒在土壤中的存活与传播进行了系统分析,并探究了病毒在土壤中吸附与存活的主要影响因素.结果表明:流感病毒、肠道病毒、甲型肝炎病毒和冠状病毒均能在土壤中存活较长时间,并能以土壤为介质进行传播,进而导致人体暴露;土壤微生物、含水量、土壤类型及温度是影响病毒在土壤中吸附与存活的主要因素,土壤微生物的存在、含水量的降低以及温度的升高可能阻碍病毒在土壤中的存活,黏粒含量及pH较高的土壤中病毒的吸附量与存活率较高,而金属氧化物及有机质含量较高的土壤中病毒的吸附量与存活率较低.基于上述分析,对病毒在土壤中存活与传播的研究提出了有针对性的建议,如系统开展我国土壤病毒的调查研究,加强病毒在土壤中存活、传播规律及影响因素的研究等.研究显示,土壤在病毒的环境传播过程中具有重要作用,不可忽视病毒经土壤传播产生的风险.      

病毒在无生命物体表面存活时间及其影响因素分析

2020年3月11日,世界卫生组织宣布新型冠状病毒肺炎（COVID-19,简称“新冠肺炎”）疫情全球大流行.病毒性传染病在人群中的发生需具备3个相互关联的条件,即传染源、传播途径和易感人群,其中传播途径是一个关键环节.从环境传播的角度,综述了包括SARS（重症急性呼吸综合征）病毒、MERS（中东呼吸综合征）病毒等病毒在无生命物体表面的存活时间及影响因素.结果表明:包括冠状病毒在内的一些具有传染性的病毒能在多种无生命物体表面存活一定时间,进而可能通过物体表面进行环境传播,造成潜在的健康风险;物体材质、温度、湿度以及病毒载量等因素是影响病毒在无生命物体表面存活的主要因素.在上述分析的基础上,对医疗废物和生活垃圾的收集、运输、处理等过程提出了针对性的防控措施,以期对新型冠状病毒（2019-nCoV）以及未来可能出现的其他病毒的环境传播防控对策提供参考.