城市环境总体规划中大气环境红线内涵及划定技术

城市环境总体规划是一项重大环境管理制度创新,目前全国已启动了24个城市的环境总体规划编制工作,其中划定环境红线是城市环境总体规划的核心内容。本文结合福州、宜昌、平潭等城市环境总体规划编制实践,首次提出了大气环境红线的技术框架,将大气环境红线划分为源头布局敏感区、污染易聚集区及敏感的环境受体三类,并创新性建立了大气环境红线划定技术方法,初步构建了适用于城市环境总体规划的空间规划技术体系。     

Potentially toxic metal contamination of urban soils and roadside dust in Shanghai, China

A detailed investigation was conducted to understand the contamination characteristics of a selected set of potentially toxic metals in Shanghai. The amount of Pb, Zn, Cu, Cr, Cd and Ni were determined from 273 soil/dust samples collected within urban area. The results indicated that concentration of all metals except Ni in soils was significant, and metal pollution was even severer in roadside dust. A series of metal spatial distribution maps were created through geostatistical analysis, and the pollution hotspots tended to associate with city core area, major road junctions, and the regions close to industrial zones. In attempt of identifying the source of metals through geostatistical and multivariate statistical analyses, it was concluded as follows: Pb, Zn and Cu mainly originated from traffic contaminants; soil Ni was associated with natural concentration; Cd largely came from point-sourced industrial pollution; and Cr, Ni in dust were mainly related to atmospheric deposition.     

Comparison of two metal surveys by moss Tortula ruralis in Budapest, Hungary

Moss transplants of Tortula ruralis were used as active biomonitoring organisms as part of a monitoring study to assess the metals (Al, Cd, Cu, Cr, Fe, Ni, Pb, V and Zn) associated with ambient particles on mosses in Budapest, the capital town of Hungary. The moss samples were collected in a nature conservation area from a semi-arid sand grassland (Festucetum vaginatae danubiale), less than 1 month before transplantation. Moss cushions were exposed to pollution in Budapest during October–November 1993 and February–March 1994. In the study area, 16 sites were marked out as measuring sites, in accordance with the structure of the city. A similar stand was established in the Botanical Gardens of the Szent István University in Gödöll? as a control site. ICP-AES analysis of moss for metals showed the ability of Tortula ruralis to accumulate the metals under study. Control site showed lower impact in comparison to the other sites.     

Suspended Particulate Matter Distribution in Rural-Industrial Satna and in Urban-Industrial South Delhi

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM₁₀), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM_2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM_2.5, PM₁₀, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m⁻³ and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m⁻³. Values at Delhi were well above the standard limit for 24-h PM_2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m⁻³), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM_2.5 standards. The position of PM₁₀ in Delhi is drastic and needs an immediate attention. PM₁₀ levels at Delhi were also well above the standard limit for 24-h PM₁₀ National Ambient Air Quality Standards (NAAQS; 150 μg m⁻³), while levels at Satna remained under the standard limit. PM_2.5/PM₁₀ values were also calculated to determine PM_2.5 contribution. At Satna, PM_2.5 contribution to PM₁₀ was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m⁻³). At Satna, the PM₁₀ contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM₁₀, PM_2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.     

Spatial & temporal variations of PM10 and particle number concentrations in urban air

The size of particles in urban air varies over four orders of magnitude (from 0.001 μm to 10 μm in diameter). In many cities only particle mass concentrations (PM10, i.e. particles <10 μm diameter) is measured. In this paper we analyze how differences in emissions, background concentrations and meteorology affect the temporal and spatial distribution of PM10 and total particle number concentrations (PNC) based on measurements and dispersion modeling in Stockholm, Sweden. PNC at densely trafficked kerbside locations are dominated by ultrafine particles (<0.1 μm diameter) due to vehicle exhaust emissions as verified by high correlation with NOx. But PNC contribute only marginally to PM10, due to the small size of exhaust particles. Instead wear of the road surface is an important factor for the highest PM10 concentrations observed. In Stockholm, road wear increases drastically due to the use of studded tires and traction sand on streets during winter; up to 90% of the locally emitted PM10 may be due to road abrasion. PM10 emissions and concentrations, but not PNC, at kerbside are controlled by road moisture. Annual mean urban background PM10 levels are relatively uniformly distributed over the city, due to the importance of long range transport. For PNC local sources often dominate the concentrations resulting in large temporal and spatial gradients in the concentrations. Despite these differences in the origin of PM10 and PNC, the spatial gradients of annual mean concentrations due to local sources are of equal magnitude due to the common source, namely traffic. Thus, people in different areas experiencing a factor of 2 different annual PM10 exposure due to local sources will also experience a factor of 2 different exposure in terms of PNC. This implies that health impact studies based solely on spatial differences in annual exposure to PM10 may not separate differences in health effects due to ultrafine and coarse particles. On the other hand, health effect assessments based on time series exposure analysis of PM10 and PNC, should be able to observe differences in health effects of ultrafine particles versus coarse particles.     

上海城区交通干道黑碳污染调查

采用设置在上海市中心城区交通主干道旁空气质量自动监测站2018年1—12月的观测数据,分析黑碳气溶胶(BC)污染特征及其与PM_(2.5)、SO_2、NO_x、CO、O_3、苯、甲苯、乙苯、二甲苯和气象参数的相关性。结果表明,观测期间内,BC小时均值为(3 038±22) ng/m~3,ρ(BC)在ρ(PM_(2. 5))中占比为(11. 48±0. 12)%。日内ρ(BC)变化呈双峰型,各月份之间ρ(BC)变化不大。ρ(BC)与风速呈负相关,与PM_(2. 5)、NO_x、CO、苯、甲苯、乙苯和二甲苯呈正相关。     

长江中游城市群经济与生态成本空间演化模式分析

综合运用变异系数、泰尔指数及ESDA-GIS多种方法,在充分考虑传统经济影响因子的基础上,尝试引入经济发展生态成本指标,分析长江中游城市群经济综合发展水平与生态成本的空间匹配及演化模式。研究表明:经济综合发展水平高低聚集特征明显,空间极化现象是导致区域经济发展不平衡的主要原因;生态成本空间集聚现象以高高集聚和低低集聚为主,且呈现出高高集聚减少、低低集聚增多的现象,生态成本消耗有所改善;2001~2012年长江中游城市群市域经济综合发展水平与生态成本表现出越来越显著的差异化空间格局,呈现出由低经济综合发展水平-低生态成本过渡到高经济综合发展水平-高生态成本,进而发展到高经济综合发展水平-低生态成本的空间匹配模式的阶段性特征;高经济综合发展水平-高生态成本的经济发展模式仍在大部分城市中存在,经济与生态空间协调发展的潜力仍然很大。     

城市能源利用与环境保护的综合管理初探

能源短缺和环境污染已成为中国推行全面协调可持续发展的重要制约因素,作为能源消耗的主体和环境污染的控制重点,在城市层面推动能源发展战略的转变和强化环境保护是发展的基本要求.鉴于能源与环境之间的高度关联性,在管理方面要求对能源发展和环境保护进行统筹考虑和综合管理,充分强调能源经济效率和环境制约因素在能源发展中的作用.通过制定合理的产业能效标准和排放绩效标准,为城市经济、能源和环境的可持续性发展提供科学性、系统性决策支持.     

大连城市环境评价与城市发展定量研究

通过对大连城市环境系统的考察,设立了完整的评价指标体系,运用模糊优选理论建立模糊评价模型,对大连城市环境进行了定量研究,并结合经济和城市化情况进行了分析。研究结果表明:城市环境质量总体上是在逐年提高的,但从2002年以来发展较为平缓。经济和城市化情况有较大发展,但仍有不足之处。     

长株潭城市群生态宜居水平综合评价

随着长株潭城市群工业化进程加快,其经济发展水平和城镇化水平得到飞速的提升,但是生态环境和宜居环境受到较大影响.基于层次分析法,从生态环境、资源节约、公共配套、社会民生4个维度构建生态宜居综合评价指标体系,综合测度2010～2018年长株潭城市群的生态宜居水平.结果显示2010～2018年间,长株潭城市群生态宜居综合水平...