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.     

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.      

闽江河口养虾塘养殖期和非养殖期CO2通量变化特征

为揭示河口区陆基养虾塘从养殖期到非养殖期一年间的CO₂通量变化,以福建省闽江河口鳝鱼滩陆基养虾塘为研究对象,于2016年5月-2017年3月采用悬浮箱/静态箱-气相色谱法对养虾塘养殖期水-大气界面和非养殖期沉积物-大气界面白天CO₂垂直通量进行原位观测.结果表明:①养虾塘在整个研究期间CO₂通量变化范围为-62.87~162.81 mg/（m2·h）,平均值为（42.66±18.12）mg/（m2·h）,总体上表现为大气CO₂的释放源,且呈非养殖期CO₂通量平均值[（78.51±16.61）mg/（m2·h）]显著高于养殖期[（17.98±18.26）mg/（m2·h）]的特征.②养殖期间,养虾塘CO₂通量呈"排放-吸收"交替变化的特征,而非养殖期养虾塘一直是大气CO₂的净排放源.③养虾塘养殖期CO₂通量时间变化特征主要受到ρ（DOC）（DOC为总溶解有机碳）、ρ（SO₄2-）、ρ（Cl-）、盐度、pH、ρ（Chla）（Chla为叶绿素a）的影响,其中,pH和ρ（SO₄2-）是其主要影响因子,而ρ（TDN）（TDN为总溶解氮）、ρ（TDP）（TDP为总溶解磷）、ρ（SO₄2-）对非养殖期CO₂通量时间变化影响较大.研究显示,滨海陆基养殖塘是大气CO₂的重要来源,其排放通量多低于河流、水库等水生生态系统,但高于湖泊生态系统;养殖塘CO₂通量受人为影响明显,其较高的变异性与养殖生物、饲料投放以及浮游藻类有关.      

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。     

不同制备温度下污泥生物炭对Cr(Ⅵ)的吸附特性

以城市剩余污泥为原料,于300,400,500,600 ℃温度条件下制备生物炭,通过单因素静态吸附实验探讨制备温度对生物炭吸附Cr（Ⅵ）的影响。结果表明:在500 ℃以内随着温度上升制备的生物炭对Cr（Ⅵ）的吸附量增加,制备温度高于500 ℃后变化不明显;扫描电镜（SEM）、比表面积（BET）、傅里叶红外光谱（FTIR）表征结果显示,热解温度对生物炭表面形貌和官能团组成有显著影响;等温模型及动力学拟合结果表明,生物炭吸附Cr（Ⅵ）为单分子层吸附、物理-化学复合吸附。热解温度对污泥制备生物炭吸附Cr（Ⅵ）的性能有显著影响,最佳制备温度为500 ℃,在此条件制备的生物炭对Cr（Ⅵ）的理论吸附量可达7.93 mg/g。     

应用改良型水质综合指数法评价饮用水水质

应用1套改良型水质综合指数法对3种不同类型的饮用水水质进行评价。将选取的26项检测指标按照卫生学意义分为5大类,并对各分类指标赋权。选用内梅罗法和最差因子判别法与五色等级分级法结合对2017年4—8月的3种类型饮用水进行水质评价。除7月和8月的管网水水质为2级（水质综合指数>0.5,蓝色）以外,其余月份的出水水质均达到1级（绿色）评价标准。不同类型饮用水中对水质综合指数影响最大的水质分类指标均是有机污染指标。2种不同类型的净水机出水水质均优于管网末梢水,但需注意个别指标的污染。     

博斯腾小湖最低生态水位与水量盈缺分析

近年来,博斯腾湖小湖水位大幅波动引发了湖区生态环境问题,基于最低生态水位的湖泊水量盈缺分析对小湖水量调度和生态保护有积极意义。基于1991—2019年达吾提闸实测小湖水位数据,结合湖盆DEM数据和遥感NDVI数据,分别采用年保证率设定法、湖泊地形分析法和曲线相关法计算小湖区最低生态水位;并利用其他水文、气象和农业活动和湖区水量调控数据,使用主成分分析法解析小湖缺水的主要驱动因子。结果表明:博斯腾湖小湖最低生态水位为1047.18 m,多年平均满足率为31.03%。1991—1998年、2005—2015年和2017年间博斯腾小湖区发生了生态缺水,平均缺水量为0.69×108 m3。上游来水量是小湖生态需水保证情势的主要驱动因素,农业活动和宝浪苏木水量调节活动次之,气候变化影响相对较小。2000年之前,生态缺水主要由湖区水位调控产生;2000年之后,灌区农业取水成为生态缺水主要诱因。该研究结果可以为博斯腾湖小湖水量调控和湿地生态系统恢复保护提供科学依据。