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.     

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.     

生态调控后贵州花溪水库浮游植物群落结构的变化特征及影响因素

为了解生态调控后花溪水库浮游植物功能群变化特征与环境因子的关系,基于浮游植物功能群、NMDS（非度量多维尺度分析）、RDA（冗余分析）、Pearson相关性分析方法,于2017年3月-2018年3月逐月对浮游植物群落结构与水环境指标进行采样分析.结果表明:①生态调控前,花溪水库共鉴定浮游植物4门18种,共归类出10个功能群,且功能群H1占绝对优势,其代表藻种为水华束丝藻（Aphanizomenon flosaquae）;生态调控后,共鉴定浮游植物6门66种,共归类出20个功能群,主要优势功能群为B/Lo,其代表藻种为小环藻（Cyclotella sp.）和多甲藻（Peridinium sp.）.②生态调控后,花溪水库优势功能群结构发生了变化,其变化特征为B/Lo（春季）→D/B/Lo/X2/N/P（夏季）→D/B/Lo/N（秋季）→D/MP/B/Lo/W1/W2（冬季）.功能群B的生物量在春季达到峰值（3 056.3 μg/L）,与其对低营养环境有良好的耐受性有关;功能群Lo的生物量在秋季达到峰值（2 900.9 μg/L）,与组成功能群Lo的甲藻特性有关.③RDA结果表明,生态调控前影响浮游植物生长的环境因子为SD（透明度）、ρ（DIN）（DIN为无机氮）;生态调控后影响浮游植物生长的环境因子为WT（水温）、ρ（DO）、ρ（DIN）.研究显示,生态调控后花溪水库功能群结构发生了明显变化,影响功能群变化的主要环境因子为WT和ρ（DO）.      

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.      

某垃圾焚烧厂投产前后周边土壤二英类化合物的分布

为研究垃圾焚烧厂运行对周边土壤二英类化合物（PCDD/Fs）含量的影响,采集了珠三角地区某垃圾焚烧厂投产前和投产后周边土壤样品,分析研究了该垃圾焚烧厂运行对周边土壤中PCDD/Fs含量和组分的变化.结果表明:①2012年（投产前）珠三角地区某垃圾焚烧厂周边土壤PCDD/Fs含量较低,范围为163~591 ng/kg（毒性当量范围为0.198~0.863 ng I-TEQ/kg,I-TEQ为国际毒性当量因子折算的毒性当量值）;2017—2019年（投产后）周边土壤PCDD/Fs含量范围为151~1.75×103 ng/kg（毒性当量范围为0.812~3.88 ng I-TEQ/kg）,与其他研究相比处于较低的水平.②投产后,距该垃圾焚烧厂较近（1.5 km）的采样点（S1）土壤PCDD/Fs含量逐年增长,在较远（5.2 km）但人口较密集的采样点（S3）土壤PCDD/Fs含量整体较高,但呈逐年下降趋势.③投产后,土壤中的17种PCDD/Fs单体组分中,毒性当量贡献率最高的单体为八氯二苯并二英（OCDD）和2,3,4,7,8-五氯二苯并呋喃（2,3,4,7,8-PeCDF）,二者毒性当量贡献率范围为15.7%~45.4%.④在同一采样点土壤PCDD/Fs单体组分年间差异不明显,但同一年份不同采样点差异明显.研究显示,目前该垃圾焚烧厂周边土壤PCDD/Fs含量较低,但仍需要长期监测其可能带来的风险.      

新冠肺炎疫情期间我国居民佩戴口罩防护行为研究

口罩作为阻隔病毒传染的物理方式之一,其能阻断病原体经飞沫传播,同时具有双向隔离保护作用.佩戴口罩对于公众防范新型冠状病毒（2019-nCoV）感染的风险和维持人体基本健康具有重要意义.为了解新型冠状病毒肺炎（COVID-19,简称“新冠肺炎”）疫情期间我国居民佩戴口罩的行为模式特征,基于新冠肺炎疫情期间我国人群环境暴露行为模式调查,分析全国31个省（自治区、直辖市）居民在新冠肺炎疫情期间佩戴口罩的行为特征,并探讨不同潜在风险人群佩戴口罩行为模式的差异性.结果表明:①在新冠肺炎疫情期间,我国人群外出佩戴口罩的比例在99%以上,显著高于非疫情期间的口罩佩戴率（16.05%）,其中,医务人员以及与人群广泛接触群体的口罩佩戴率最高（100%）.②居民以仅佩戴医用外科口罩、仅佩戴一次性使用医用口罩以及佩戴医用外科口罩和一次性使用医用口罩3种模式为主,占31种口罩佩戴模式的60%以上.③新冠肺炎疫情期间,不同职业人群、不同所属人群以及不同疫情地区人群佩戴口罩的比例均存在显著差异.④新冠肺炎疫情期间,我国居民佩戴口罩的更换频次多为累计使用时长4 h更换一次和累计使用时长24 h更换一次.⑤人群外出佩戴口罩的比例随新冠肺炎疫情严重程度的升高而增加.尽管新冠肺炎疫情分布特征和管控措施存在差异,但居民佩戴口罩行为均表现良好,其中居住地不存在疑似病例的人群比居住地存在疑似病例的人群的口罩佩戴率更高,说明人群佩戴口罩行为与疫情的发展可能存在一定的相互作用.研究显示,新冠肺炎疫情期间我国人群佩戴口罩这一防护行为总体执行较好.      

新冠肺炎疫情期间我国居民洗手行为研究

直接接触和飞沫传播等方式是新型冠状病毒传播的主要途径,合理的洗手行为是切断暴露途径和降低病毒感染风险的有效防控措施,对于新型冠状病毒肺炎（COVID-19,简称“新冠肺炎”）疫情的防控具有重要的作用.该研究于2020年2月25日—3月14日,采用电子问卷的方式调查了覆盖我国31个省（自治区、直辖市）1 728个县（区）18岁及以上的居民,收集共计8 330名成人的洗手情形及洗手时长等信息,分析不同暴露情景下的洗手行为及其影响因素.结果表明:女性、城市地区居民在洗手比例和洗手时长上均分别高于男性、农村地区居民.人群在一般暴露情景下的洗手比例较高,而对于病毒感染风险较高的暴露情景（如咳嗽或打喷嚏后、接触他人后等）的洗手率（分别为73.6%和83.9%）排名靠后,说明人群对病毒的传播途径和防护措施有待深入理解;在洗手时间上,根据WHO规定的洗手时长标准（20 s）,仅有41.7%的人群洗手时长合格（大于20 s）,城区居民洗手时长的合格率（42.0%）显著高于农村地区（39.7%）;总体上,具有外出经历的人群洗手比例较未曾外出的人群高,新冠肺炎疫情期间居住地是否存在新冠肺炎疑似和确诊病例显著影响居民的洗手行为,但是疫情最严重的地区居民的洗手时长合格率（37.2%）最低,反而疫情最轻的地区居民的洗手时长合格率（43.6%）最高,说明居民的洗手行为可能受疫情等多方面的影响.研究显示,相比于非疫情期间而言,疫情期间我国居民洗手行为发生率提高,洗手时长合格率提高,但是仍然水平偏低.应提高居民洗手行为意识,科学地执行洗手这一防护措施,相关政策制定以及个人防护应当进一步关注和重视洗手行为的防疫作用.      

2006-2017年四川盆地MODIS气溶胶光学厚度时空变化特征

四川盆地地形复杂、气候特殊,是我国颗粒物污染高发地.为探究四川盆地气溶胶分布和周期变化特征,深入认识气溶胶污染特性及其气候效应,结合卫星遥感探测方法,利用2006-2017年MODIS C006 3 km AOD（气溶胶光学厚度）产品,分析了四川盆地AOD的时空特征.结果表明:①MODIS AOD（MODIS数据反演的气溶胶光学厚度）与太阳光度计CE318观测的AOD、ρ（PM_2.5）、ρ（PM₁₀）线性相关系数分别为0.78、0.77、0.75,表明MODIS C006 3 km AOD产品适用于四川盆地颗粒物污染研究.②四川盆地AOD平均值范围为0.1~1.3,其中,成都平原和四川盆地东南部地区是AOD高值（AOD值>1.0）中心,四川盆地周边高海拔区AOD均小于0.3.③2006-2017年AOD年均值范围为0~2.5,整体呈"倒N型"曲线下降,其峰值和谷值分别出现在2013年和2017年;2013年AOD大于1.0的区域占四川盆地的34.1%,是12 a中颗粒物污染最重的一年;2017年AOD小于0.3的面积占57.1%.④AOD季节性变化呈春季最大、夏季次之、秋季最小的特征.⑤AOD月变化呈"双峰型"波动特征,AOD月均值范围为0~2.5,其中,2-5月AOD月均值均大于0.7,8月AOD月均值为0.6,11-12月AOD月均值均小于0.5.研究显示,四川盆地颗粒物污染防治应以成都平原城市群和四川省南部城市群为主,应重点控制细颗粒物排放,合理安排工业企业的周期性生产强度.      

达里诺尔湖水体DOM荧光特征及其来源解析

达里诺尔湖（简称“达里湖”）是内蒙古自治区高原地区重要的生态屏障,探究达里湖水质状况及污染来源,对加强流域水环境治理、改善水环境质量具有十分重要的意义.于2018年9月及2019年6月对湖水进行采样,并通过三维荧光光谱结合PARAFAC（平行因子分析）模型,探究达里湖水体DOM（溶解性有机质）来源及其与水质的关系.结果表明:①达里湖水体中pH较高,ρ（DOC）（DOC为溶解性有机碳）、ρ（NH₄+-N）、ρ（TP）相对较高,均超过GB 3838—2002《地表水环境质量标准》Ⅴ类水质标准限值.②水体中DOM含4种荧光组分.夏季水体DOM主要分布于河流入湖口附近,其中,类腐殖质荧光组分（紫外区类富里酸和可见区类富里酸）占总组分的62.93%,类蛋白类荧光组分（类色氨酸和类酪氨酸）占总组分的36.07%;秋季水体DOM主要分布于东南侧,其中,类腐殖质荧光组分占总组分的40.52%,类蛋白类荧光组分占总组分的59.48%.③达里湖采样点荧光参数表明,达里湖DOM自生源特征较强,腐殖化程度较低.类腐殖质荧光组分与ρ（DOC）、ρ（Chla）均呈正相关,类色氨酸荧光组分与pH呈正相关,类络氨酸与ρ（DTN）、ρ（NH4+-N）、ρ（DTP）均呈正相关.研究显示,达里湖DOM具有陆源与生物源双重特性,DOM的形成与微生物、细菌、浮游生物的生命活动密切相关.