Primary and secondary components of PM2.5 in Milan (Italy)

In sampling campaigns--carried out by means of a high-volume gravimetric sampler--performed between August 2002 and December 2003, 24-h PM2.5 samples have been collected at an urban background site in downtown Milan and analyzed for elemental and organic carbon, ionic species (i.e., chloride, nitrates, sulfates and ammonium) and some elemental species. Chemical speciation data are evaluated also in terms of primary and secondary components of fine particulate matter: in particular, the contribution of secondary organic aerosols (SOA) and of the primary contribution from traffic to observed PM2.5 concentration levels are evaluated by means of the EC tracer method.     

Wintertime indoor air levels of PM10, PM2.5 and PM1 at public places and their contributions to TSP

From 26 October 2002 to 8 March 2003, particulate matter (PM) concentrations (total suspended particles [TSP], PM10, PM2.5 and PM1) were measured at 49 public places representing different environments in the urban area of Beijing. The objectives of this study were (1) to characterize the indoor PM concentrations in public places, (2) to evaluate the potential indoor sources and (3) to investigate the contribution of PM10 to TSP and the contributions of PM2.5 and PM1 to PM10. Additionally, The indoor and outdoor particle concentrations in the same type of indoor environment were employed to investigate the I/O level, and comparison was made between I/O levels in different types of indoor environment. Construction activities and traffic condition were the major outdoor sources to influence the indoor particle levels. The contribution of PM10 to TSP was even up to 68.8%, while the contributions of PM2.5 and PM1 to PM10 were not as much as that of PM10 to TSP.     

Fine Particulate Pollution Characteristics in Jinan City

The characteristics of fine particulate pollution(PM10and PM25)were measured at urban and suburban sites in Jinan during the 2008-2009 heating and non-heating seasons.The results showed that PM10 and PM2.5 pollution was quite serious,and PM mass concentration was higher during the heating season than the non-heating season.PM was the highest in the chemical factory and lowest in the development zone.The mass concentrations of PM10 and PM2.5 were linearly related,and the mass concentration ratio of PM2.5/PM10 was up to 0.59 in urban areas.PM pollution in Jinan was related to local meteorological factors: PM2.5 mass concentration and humidity were positively correlated,and PM2.5mass concentration was negatively correlated with both click on the temperature and wind speed,although wind speed varied more.     

Comparative overview of indoor air quality in Antwerp, Belgium

This comprehensive study, a first in Belgium, aimed at characterizing the residential and school indoor air quality of subgroups that took part in the European Community Respiratory Health Survey and the International Study of Asthma and Allergy in Childhood [Masoli M, Fabian D, Holt S, Beasley R. Global Burden of Asthma, Medical Research Institute of New Zealand, University of Southampton; 2004.] questionnaire-based asthma and related illnesses studies. The principal aim was to perform a base-line study to assess the indoor air quality in Antwerp in terms of various gaseous and particulate pollutants. Secondly, it aimed to establish correlations between these pollutants investigated, the pollutant levels in the indoor and outdoor micro-environments, findings of the previous questionnaire-based studies and an epidemiological study which ran in conjunction with this study. Lastly, these results were compared and evaluated with current indoor and ambient guidelines in various countries This paper presents selected results on PM1, PM2.5 and PM10 mass concentrations and elemental C estimates as black smoke, as well as gaseous NO(2), SO(2), O(3) and BTEX concentrations of 18 residences and 27 schools. These are related to current guidelines of Flanders, Germany, Norway, China and Canada and evaluated with reference to selected similar studies. It was found that indoor sources such as tobacco smoking and carpets, the latter causing re-suspension of dust, are responsible for elevated indoor respirable particulate matter and place school children and residents at risk. Both PM2.5 and PM10 equalled or exceeded the current guidelines adopted by Flanders, noting that 12-h and 24-h PM2.5 were compared with an annual limit value. Indoor and ambient NO(2) concentrations in the school campaign were higher than the annual EU ambient norm. The other studied pollutant levels were below the current guidelines.     

贵阳市主城区空气质量指数时空分布特征

为了解贵阳市主城区空气质量指数的时间分布和空间分布特征，采用时间序列法和插值法统计分析了2013~2015年贵阳市9个空气自动监测点SO2、NO2、PM10、PM25、CO的监测数据。结果表明：2013~2015年期间，贵阳市主城区空气质量整体良好,优于Ⅱ级空气质量标准，IAQISO2、IAQINO2、IAQIPM10、IAQIPM25、IAQICO的年均值呈现降低趋势, 空气污染物得到一定的控制；季节变化和月变化分析表现出冬季空气质量最差，夏季最好的特征。春节半月ISO2、IAQINO2、IAQIPM10、IAQIPM25的均值好于冬季均值，反映了工业和交通污染源的主控作用。空间分布上，IAQISO2、IAQINO2、IAQIPM10、IAQIPM25、IAQICO呈现“市区高，郊区低”的分布特征，空气质量指数较高的区域集中在贵阳市主城区中部和东北部     

Characterization of water-soluble ion species in urban ambient particles

Concentrations and distributions of water-soluble ion species contained in ambient particles were measured in a coastal urban area, Kaohsiung City, Taiwan. PM10 and PM2.5 samples were collected using a dichotomous sampler from November 1998 to April 1999 and were analyzed for water-soluble ion species with ion chromatography. On the average, ion species measured in this study accounted for 42.2% of the PM2.5 and 35.7% of the PM10. It was found that SO4(2-) , NO3-, and NH4+ dominated the identifiable components within both fine (PM2.5) and coarse (PM2.5-10) fractions, and occupied 90.0% and 80.6% of total dissolved ionic concentrations for PM2.5 and PM10. The secondary aerosol formed through the NOx/SO2 gas-to-particle conversion was estimated based on the oxidation ratio of sulfur and nitrogen (SOR and NOR, respectively), i.e., sulfate sulfur/nitrate nitrogen to total sulfur/total nitrogen. The average SOR/NOR values were 0.25/0.07 and 0.29/0.12 for PM25 and PM10, respectively. The high SOR and NOR values obtained in this study suggested that there existed a secondary formation of SO4(2-) from SO2 along with NO3- from NOx in the atmosphere.     

Evaluation of genotoxic and non-genotoxic effects of organic air pollution using in vitro bioassays

In this study, organic extracts of total suspended particles (TSP) and the particulate matter (PM) with the size below 2.5 microm (PM(2.5)) combined with organic extracts of the gas phase (GP) collected at two urban and two background localities were analyzed with a bacterial genotoxicity test, SOS chromotest, and an in vitro test for the dioxin toxicity determination, using a modified cell-line of rat hepatoma H4IIE.luc. In addition, the samples of TSP and GP were analyzed for PAHs contents. The PAHs concentrations and both of the toxic activities at the urban localities were much higher than ones at the background localities. Predominantly, traffic was a source of the urban air pollution there which was also confirmed by the evaluation of portions of certain PAHs (BaP/BPE, PYR/BaP) at the localities. On the other hand, the background localities were apparently affected by a long-distance transport of the pollutants from urban and industrial centers. The results of the bioassays indicated potential health risks for the population exposed to the organic air pollutants, especially at the urban localities. Based on the collected samples, distribution of the organic pollutants with the toxic effects in the air was evaluated. The significant portion of the direct genotoxins was bound to the particles larger than 2.5 microm. On the contrary, the indirect genotoxins were bound predominantly to the particles with the size below 2.5 microm. However, in the urban air they may be also bound to the larger particles, as well. While the direct genotoxicity may be related with the presence of PAH-derivatives as well as some polar organic pollutants, the indirect genotoxicity is related with the detected carcinogenic PAHs. But besides the above specified pollutants it is also necessary to consider the presence of other toxic components of the complex organic air pollution mixture that may also show potential health risks. This study demonstrates application of the combination of the screening bioassays for the evaluation of organic air pollution and identification of its health risks.     

Using air pollution based community clusters to explore air pollution health effects in children

To study respiratory health effects of long-term exposure to ambient air pollutant mixture, we observed 7058 school children 5-16 years of age living in the four Chinese cities of Lanzhou, Chongqing, Wuhan, and Guangzhou. These children were enrolled from elementary schools located in eight districts, one urban district and one suburban district in each of the above cities. Ambient levels of PM(2.5), PM(10-2.5), total suspended particles (TSP), SO(2), and NO(x) were measured in these districts from 1993 to 1996. Based on a cluster analysis of arithmetic mean concentrations of PM(2.5), PM(10-2.5), (TSP-PM(10)), SO(2), and NO(x), we classified these children into four ordinal categories of exposure to ambient air pollutant mixtures. We tested for exposure-response relationships using logistic regression models, controlling for relevant covariates. We observed monotonic, positive relationships of exposure to the pollutant mixture with prevalence rates of cough with phlegm and wheeze. Other outcomes were not associated with the exposure in a monotonic exposure-response pattern. Even so, odds ratios for cough, phlegm, bronchitis, and asthma in the higher exposure district clusters were all higher than in the lowest exposure district cluster. We found evidence that exposure to the pollutant mixtures had adverse effects on children living in the four Chinese cities.     

Spatial variation of PM elemental composition between and within 20 European study areas — Results of the ESCAPE project

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements.We measured PM_2.5 and PM₁₀ in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM_2.5 and PM₁₀ filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning.PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM_2.5 and from 0.93 (V) to 2.28 (Cu) for PM₁₀.Our selected PM elements were variably correlated with the main pollutants (PM_2.5, PM₁₀, PM_2.5 absorbance, NO₂ and NO_x) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM₁₀_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO₂ and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM.     

Particulate matter and black smoke concentration levels in central Athens, Greece

This study presents the statistical analysis of PM(10) and PM(2.5) concentrations (measured at a central site, in the Athens area), along with black smoke (BS) data, for a 2-year period. The biennial average concentrations of PM(10) and PM(2.5) were 75 and 40 microg m(-3). The respective average concentration of BS, as estimated by the OECD method, was 108 microg m(-3). Severe exceedances of the PM(10) air quality standards were recorded. The seasonal variation of PM(10) and BS was less pronounced than the variation of PM(2.5), which concentration was elevated by 14.2% during the cold period. Concentrations of all three pollutants were significantly lower during weekends; however, PM(2.5) and BS displayed a more uniform weekly distribution pattern. PM(10) particles were found to be almost equally comprised by PM(2.5) and PM(10-2.5) particles (PM(2.5)/PM(10) ratio=0.53+/-0.09 microg/m(3)). The average PM(10)/BS value was found lower than unity revealing the inappropriateness of the used reflectance conversion method, for the estimation of mass-equivalent BS concentrations, in the study area, where diesel-powered vehicles mainly control emissions of light-absorbing substances. Important reductions in concentrations were observed during days when drivers of diesel-powered taxies and transportation buses went on strike (reaching 40% for BS). Calm wind conditions were found to have an incremental effect on particle concentrations and were also associated with the appearance of persistent episodic events. Increased PM levels were also observed during southern-southwestern wind flows while significantly lower-than-average concentrations were measured during precipitation events. Separate regression analyses were performed for PM(10), PM(2.5) with BS and NO(x) as independent variables, in an attempt to estimate the relative contribution of specific source types (diesel-powered vehicles) to measured particle levels. The contribution of the diesel-exhaust component to PM(10) mass was estimated at 49.9%, while the corresponding contributions to PM(2.5) mass concentrations was 53.8%. These results may have important implications with the oncoming decision of national authorities to allow the purchase of diesel-powered private cars to the residents of the Greater Athens Area, which was forbidden up to this day.     

Levels of household particulate matter and environmental tobacco smoke exposure in the first year of life for a cohort at risk for asthma in urban Syracuse, NY

The Syracuse, NY, AUDIT (Assessment of Urban Dwellings for Indoor Toxics) study was designed to quantify asthma agent levels in the inner-city homes of a birth cohort whose mothers had a diagnosis of asthma. Risk of exposure to particulate matter (PM), particle number and tobacco smoke was assessed in 103 infants' homes. Repeat measurements were made in 44% of the homes. Infants also were examined on a quarterly basis during the first year of life to monitor their respiratory health and urine cotinine levels. Overall geometric mean (GM) values for PM(2.5) of 21.2 μg/m(3) and for PM(10) of 31.8 μg/m(3) were recorded in homes at visit 1. GM values for PM(2.5) and PM(10) in smoking homes were higher at 26.3 and 37.7 μg/m(3), while values in non-smoking homes were 12.7 and 21.2 μg/m(3) respectively. Fifty-four percent of mothers (55/103) smoked at some point in pregnancy (39% smoked throughout pregnancy). Environmental tobacco smoke (ETS) exposure occurred in 68% of homes during the infants' first year. Significant to this study was the size- and time-resolved monitoring of PM at 140 home visits and the classification of PM count data. PM number counts ranged from continuously low levels (little indoor activity) to continuously high counts (constant indoor activity), and recorded apparent instances of prolonged repeated cigarette smoking. Wheezing in the first year of life was recorded for 38% of the infants (39/103). Adjusted logistic regression modeling demonstrated that elevated levels of indoor PM(2.5) (≥ 15 μg/m(3)) were a significant risk factor for infant wheezing after controlling for infant gender, mothers' age and education level, season of home visit and presence of carpeting (OR 4.21; 95% CI 1.36-13.03; p=0.013). An elevated level of the nicotine metabolite cotinine in infant urine also was associated with infant wheezing after adjusting for infant gender, mothers' age and education level (OR 5.10; 95% CI 0.96-27.24; p=0.057). ETS exposure was pervasive in the AUDIT cohort and a risk for developing infants in this urban population.     

WATCH

Abstract

The characteristics of fine particulate pollution (PM₁₀ and PM_2.5) were measured at urban and suburban sites in Jinan during the 2008–2009 heating and non-heating seasons. The results showed that PM₁₀ and PM_2.5 pollution was quite serious, and PM mass concentration was higher during the heating season than the non-heating season. PM was the highest in the chemical factory and lowest in the development zone. The mass concentrations of PM₁₀ and PM_2.5 were linearly related, and the mass concentration ratio of PM_2.5/PM₁₀ was up to 0.59 in urban areas. PM pollution in Jinan was related to local meteorological factors: PM_2.5 mass concentration and humidity were positively correlated, and PM_2.5 mass concentration was negatively correlated with both click on the temperature and wind speed, although wind speed varied more.     

Effects of travel mode on exposures to particulate air pollution

Monitoring was carried out of particulate concentrations whilst simultaneously walking and driving 48 routes in London, UK. Monitoring was undertaken during May and June 2005. Route lengths ranged from 601 to 1351 m, and most routes were travelled in both directions. Individual journey times ranged from 1.5 to 15 min by car (average 3.7 min) and 7.3 to 30 min (average 12.8 min) whilst walking; car trips were therefore repeated up to 5 times for each single walking trip and the results averaged for the route. Car trips were made with windows closed and the ventilation system on a moderate setting. Results show that mean exposures while walking are greatly in excess of those while driving, by a factor 4.7 for the coarse particle mass (PM10-PM2.5), 2.2 for the fine particle mass (PM2.5-PM1), 1.9 for the very fine particle mass (相似文献   

南昌市环境空气污染时空变化特征及影响因素研究

选取2014~2017年南昌市不同时间尺度AQI及主要空气污染物数据，利用GIS技术、神经网络分析、后向轨迹模型及地统计分析方法，分析了南昌市环境空气污染时空变化特征及影响因素。结果表明，南昌市近年来空气质量总体变化不大，空气质量等级以良为主，占全年比例为57%~61%。但首要污染物变化较大，即PM2.5比例显著下降，NO2和O3比例显著上升，PM10变化不大。南昌市空气污染季节变化显著，冬春季空气质量较差，以PM10、PM2.5污染为主，夏季空气质量最好，以O3污染为主。空气污染周变化以周末及周一污染较重、周四污染最轻，说明南昌市空气污染除了与群众出行习惯有关，还存在其他影响因素。南昌市空气质量日变化呈双峰型（9:00~11:00和20:00~22:00），主要受上、下班高峰期带来的交通尾气影响。南昌市空气污染空间变化呈典型的“郊区-市区”分布，其中AQI、PM10、PM2.5、SO2、NO2、CO值均以市区较高、郊区较低，而O3的空间分布规律正好相反，这主要与城区NOx排放较多，O3易与其迅速反应而消耗有关。后向轨迹聚类分析结果表明，来自本地的短轨迹气团占比高，对PM2.5、PM10、NO2、O3的影响大。气象因素上，PM2.5、PM10、NO2受相对湿度影响较大，O3受温度影响较大。     

合肥市PM_(2.5)浓度时空分布特征及影响因素分析

利用2017年合肥市污染监测站点PM_(2.5)浓度数据、气象数据以及土地利用类型数据,结合随机森林算法(RF)与土地利用回归模型(LUR),模拟合肥市PM_(2.5)浓度空间分布,并利用主成分分析法对PM_(2.5)影响因素进行分析。结果表明:(1)合肥市PM_(2.5)浓度日变化特征大致呈双峰变化,春季、夏季及秋季的峰值多出现在8∶00～9∶00,而冬季的峰值则出现在10∶00～11∶00。低谷值大致都出现在15∶00～17∶00。全年PM_(2.5)浓度变化趋势与春季类似。夏季PM_(2.5)浓度变化最为平稳。(2)2017年合肥市PM_(2.5)浓度分布由城市中心向外减弱,形成北高南低,西高东低的空间分布格局。(3)影响因素方面,PM_(2.5)浓度变化与降水、风速以及相对湿度等呈负相关关系,日照对PM_(2.5)浓度的影响较大,气压及其他污染物与PM_(2.5)浓度呈正相关关系,其中NO_2对PM_(2.5)浓度的影响力度较大。     

基于遥感数据的PM2.5与城市化的时空关系研究——以成渝城市群为例

采用1998~2013年卫星遥感影像反演的PM2.5全球高精度产品数据集，结合GIS空间分析、地理加权回归（GWR）以及地理探测器等方法，系统地分析了成渝城市群城市化与PM2.5分布之间的关系。结果表明：（1）1998~2013年成渝城市群城市化速度较快，城市区域的PM2.5均值明显高于非城市区域，说明城市化对PM2.5具有一定的影响；（2）近16 a PM2.5重心与城市重心整体上都向东南方向移动，且两者每年在经度上的波动方向基本相反；（3）夜间灯光数据与PM2.5在空间分布上具有较好的一致性，且1998~2013年两者的GWR全局R2在0.86~0.95之间，相关性显著，研究区内城市化和人类活动对PM2.5的分布具有明显影响；（4）地理探测分析表明不同城市化因子对PM2.5影响差异显著，从2006到2013年城区人口密度和建成区绿化覆盖率逐渐成为成渝城市群PM2.5分布的主要影响因子。     

Differentiating the effects of fine and coarse particles on daily mortality in Shanghai, China

The findings on health effects of ambient fine particles (PM2.5) and coarse particles (PM10-2.5) remain inconsistent. In China, PM2.5 and PM10-2.5 are not the criteria air pollutants, and their monitoring data are scarce. There have been no epidemiological studies of health effects of PM2.5 and PM10-2.5 simultaneously in China. We conducted a time series study to examine the acute effects of PM2.5 and PM10-2.5 on daily mortality in Shanghai, China from Mar. 4, 2004 to Dec. 31, 2005. We used the generalized additive model (GAM) with penalized splines to analyze the mortality, air pollution and covariate data. The average concentrations of PM2.5 and PM10-2.5 were 56.4 microg/m3 and 52.3 microg/m3 in our study period, and PM2.5 constituted around 53.0% of the PM10 mass. Compared with the Global Air Quality Guidelines set by World Health Organization (10 microg/m3 for annual mean) and U.S. National Ambient Air Quality Standards (15 microg/m3 for annual mean), the PM2.5 level in Shanghai was much higher. We found that PM2.5 was associated with the death rates from all causes and from cardiorespiratory diseases in Shanghai. We did not find a significant effect of PM10-2.5 on mortality outcomes. A10 microg/m3 increase in the 2-day moving average (lag01) concentration of PM2.5 corresponded to 0.36% (95% CI 0.11%, 0.61%), 0.41% (95% CI 0.01%, 0.82%) and 0.95% (95% CI 0.16%, 1.73%) increase of total, cardiovascular and respiratory mortality. For PM10-2.5, the effects were attenuated and less precise. Our analyses provide the first statistically significant evidence in China that PM2.5 has an adverse effect on population health and strengthen the rationale for further limiting levels of PM2.5 in outdoor air in Shanghai.     

Characteristics of PM10, PM2.5, CO2 and CO monitored in interiors and platforms of subway train in Seoul, Korea

This study was performed to investigate the concentration of PM(10) and PM(2.5) inside trains and platforms on subway lines 1, 2, 4 and 5 in Seoul, KOREA. PM(10), PM(2.5), carbon dioxide (CO(2)) and carbon monoxide (CO) were monitored using real-time monitoring instruments in the afternoons (between 13:00 and 16:00). The concentrations of PM(10) and PM(2.5) inside trains were significantly higher than those measured on platforms and in ambient air reported by the Korea Ministry of Environment (Korea MOE). This study found that PM(10) levels inside subway lines 1, 2 and 4 exceeded the Korea indoor air quality (Korea IAQ) standard of 150 microg/m(3). The average percentage that exceeded the PM(10) standard was 83.3% on line 1, 37.9% on line 2 and 63.1% on line 4, respectively. PM(2.5) concentration ranged from 77.7 microg/m(3) to 158.2 microg/m(3), which were found to be much higher than the ambient air PM(2.5) standard promulgated by United States Environmental Protection Agency (US-EPA) (24 h arithmetic mean: 65 microg/m(3)). The reason for interior PM(10) and PM(2.5) being higher than those on platforms is due to subway trains in Korea not having mechanical ventilation systems to supply fresh air inside the train. This assumption was supported by the CO(2) concentration results monitored in tube of subway that ranged from 1153 ppm to 3377 ppm. The percentage of PM(2.5) in PM(10) was 86.2% on platforms, 81.7% inside trains, 80.2% underground and 90.2% at ground track. These results indicated that fine particles (PM(2.5)) accounted for most of PM(10) and polluted subway air. GLM statistical analysis indicated that two factors related to monitoring locations (underground and ground or inside trains and on platforms) significantly influence PM(10) (p<0.001, R(2)=0.230) and PM(2.5) concentrations (p<0.001, R(2)=0.172). Correlation analysis indicated that PM(10), PM(2.5), CO(2) and CO were significantly correlated at p<0.01 although correlation coefficients were different. The highest coefficient was 0.884 for the relationship between PM(10) and PM(2.5).     

基于LUR模型探究城市景观格局对PM2.5浓度的影响——以长株潭城市群为例

随着城市化进程的加快，空气污染问题已成为中国最主要城市问题之一，严重影响公众健康。当前微观尺度下空气监测点周围景观格局对PM25浓度影响的研究较少，以长株潭城市群为例，选取地形、污染源、人口、道路交通、土地利用与城市景观格局6大类预测变量，其中城市景观格局选取边缘密度、连续度、形状指数、斑块平均面积、蔓延度、均匀度指数7个景观指数，运用逐步线性回归模型，探究城市景观格局对PM25浓度的影响。研究结果显示：（1）所选取的土地景观格局指数可以解释研究区PM25浓度的732%的变异，模型拟合较好；（2）影响PM25浓度的土地利用类型包括建设用地、林地、草地与水体。微观尺度下城市各类型景观格局中连续度和形状指数对PM25影响显著，建设用地连续度越高，分布越集聚，PM25浓度越高；水体形状指数越小，形状越简单规则，越易降低PM25浓度；（3）城市整体景观格局中，景观聚集程度与景观多样性等因素对PM25浓度产生重要影响。减少景观内各类型斑块的离散分布，使各景观类型均匀分布于整体景观内，有助于降低PM25浓度。研究结果可为未来大气防治与城市规划提供参考依据。〖HJ1〗〖HJ〗〖JP+1〗     

雾霾污染的城市间动态关联及其成因研究

面对严重的雾霾天气以及雾霾污染边界不断扩张的严峻挑战,加快创新大气污染联防联控体系以形成跨区域协同治污合力势在必行。本文基于京津冀、长三角、珠三角、成渝、长中游等五大地区96个城市2015年的空气质量指数(AQI)以及PM_(2.5)、PM_(10)、SO_2、CO、NO_2、O~3等6种分项污染物的逐日数据,从时间序列数据"预测能力"的视角,在向量自回归模型框架下识别雾霾污染的城市间动态交互影响效应,运用社会网络分析方法刻画雾霾污染空间关联的网络结构特征。在此基础上,运用二次指派程序从分项污染物视角考察雾霾污染空间关联的关键诱因,并利用双变量Moran指数揭示雾霾污染与其影响因素之间的空间相关性。研究发现,城市雾霾污染之间存在普遍的动态关联关系且呈现出联系紧密、稳定性强、带有明显特征的多线程复杂网络结构形态。不论在地区内部还是在全部样本城市当中,均不存在孤立的城市节点,这意味着面对雾霾污染的空间关联网络,任何一个城市都不能独善其身,均受到来自地区内部和地区以外其他城市以及它们构成的空间关联网络的影响。在六种分项污染物中,PM_(2.5)的空间关联是导致雾霾污染空间关联的最主要诱因。城市雾霾污染与其影响因素尤其是城市人口密度、投资强度、工业污染排放之间存在显著的空间相关性。基于上述结论,中国应当加快构建以防控PM_(2.5)为重点的跨区域雾霾污染协同治理机制,并将其融入城市群发展战略以及区域发展战略之中,最终实现包含雾霾污染协同治理在内的全方位的区域协同发展。