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.     

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.      

基于野外原位抽注试验和同位素技术的含水层反硝化速率研究

反硝化作用是地下水硝酸盐污染去除最重要的过程.由于水文地质条件和水文地球化学环境的复杂性和不确定性,精准测定含水层反硝化速率是反硝化过程的研究难点.选取潮白河冲洪积扇中部中国环境科学研究院地下水创新野外基地作为研究区,基于野外原位试验和15N同位素示踪法提出一种含水层反硝化速率的测定方法.该方法综合体现了研究区实际水文地质条件和水文地球化学环境对反硝化作用的影响,并充分考虑了硝酸盐在含水层中稀释弥散作用对计算结果的影响.结果表明:①潮白河冲洪积扇中部某地地下26~28 m处于还原环境,含水介质以粉细砂为主,ρ（NO₃-N）平均值为2.77 mg/L.②地下26~28 m反硝化速率在349.52~562.99 μg/（kg·d）（以N计,下同）之间,平均值为450.31 μg/（kg·d）.通过与研究区含水介质、采样深度和硝酸盐背景值相似的国内外案例对比研究,初步评估结果处于合理区间.③测试结果具有一定不确定性,主要来自忽略中间产物NO₂-和NO的计算方法、扰动采样方法、N₂O的操作规范程度及采样频率等方面.研究方法为测定含水层硝酸盐速率研究提供了新的思路,研究结果可为地下水中硝酸盐转化过程机理研究、地下水硝酸盐污染修复及风险管控提供关键的理论支撑数据.      

武当山夏季颗粒物数浓度谱分布特征及气团来源影响研究

为研究大气边界层中上层大气颗粒物的数浓度谱分布特征及气团来源的影响,于2018年6月利用3080型SMPS粒径谱仪对武当山14.6~660 nm颗粒物数浓度谱进行观测,分析和探讨了其数浓度谱分布及日变化特征,并结合后向轨迹、潜在源贡献因子法（PSCF）与浓度权重轨迹分析法（CWT）探讨对武当山颗粒物数浓度影响较大的外源输送路径和贡献源区.结果表明:①武当山大气颗粒物主要以爱根模态为主,平均数浓度为2 500个/cm3,积聚模态、核膜态平均数浓度分别为2 265、359个/cm3,3种模态数浓度分别占总数浓度的48.79%、44.21%、7.01%.②在新粒子生成日,核膜态数浓度于10:00开始上升,11:00—17:00的核膜态数浓度相对较高,约2 000个/cm3.新粒子生成日ρ（SO₂）与ρ（O₃）的日变化趋势均与核模态数浓度较为相似,表明SO₂和O₃参与光化学反应后的产物（硫酸及有机物）有利于新粒子的生成与增长.新粒子生成日风速、温度均大于非新粒子生成日,但相对湿度较低.③在东部及局地气团影响下大气颗粒物主要以积聚模态为主,数浓度分别为2 311和2 596个/cm3;核模态、爱根模态数浓度在受西北气团影响时最大,数浓度分别为806和3 078个/cm3.④潜在源区分析表明,影响武当山积聚模态数浓度的主要源区为十堰市本地及襄阳市,二者贡献值在840个/cm3以上.研究显示,武当山颗粒物主要以爱根模态为主,颗粒物数浓度日变化主要受大气边界层发展及山谷风的影响,较高的ρ（SO₂）与ρ（O₃）以及高温、低湿及较大的风速均有利于新粒子的生成,周边城市的区域性传输对武当山颗粒物的影响较大.      

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.      

嘉兴地区农村生活污水时空分布及处理设施现状分析

研究选取嘉兴市下辖农村的160座生活污水处理设施进出水为研究对象,分析了区域农村生活污水污染物时空分布特征及其处理设施现状,以期提高处理设施效率。结果表明:嘉兴市农村生活污水中氮、磷污染较有机污染更严重,ρ（COD）、ρ（TP）、ρ（TN）、ρ（NH₄+-N）年均值分别为142.23,4.02,44.19,27.74 mg/L,各污水处理设施处理效果有很大优化空间,COD、TP、TN、NH₄+-N年均去除率分别为50.5%、29.7%、36.8%、51.7%。农村生活污水空间上呈自西向东、由北至南逐渐减小的分布特征,时间上表现为冬季 > 春季 > 秋季 > 夏季。相关性分析表明,COD、TP、TN、NH₄+-N之间呈极显著正相关（P<0.01）,相关系数为0.688±0.946。设施进水C/N、NH₄+-N/TN年均值分别为3.21、68.9%,传统的单一A2/O处理工艺对低碳源污水处理效果不理想,可通过组合工艺设计、规范运营管理、加强后期监测等有效措施来进一步加强污水处理设施处理效果。