Predictions for isomer distributions of toxic dioxins and furans in selected industrial combustion processes

Three thermodynamic databases of polychlorinated dibenzo-p-dioxins and dibenzo-furans (PCDD/Fs) have been used to simulate the PCDD/F isomer distribution in industrial combustion processes. The three databases had been derived using the Group Additivity approach and two computational molecular modelling methods, Modified Neglect of Diatomic Overlap (MNDO) and Parametrized Model 3 (PM3), respectively. The predictions of the toxic PCDD/F isomer distributions using the three different databases have been compared with measured values from industrial processes. An excellent agreement between the predictions using the MNDO method and the measured data has been obtained. It is concluded that the PCDD/F isomer distributions within each group observed in these combustion processes may be thermodynamically controlled.     

Identification of PM sources by principal component analysis (PCA) coupled with wind direction data

The effectiveness of combining principal component analysis (PCA) with multi-linear regression (MLRA) and wind direction data was demonstrated in this study. PM data from three grain-size fractions from a highly industrialised area in Northern Spain were analysed. Seven independent PM sources were identified by PCA: steel (Pb, Zn, Cd, Mn) and pigment (Cr, Mo, Ni) manufacture, road dust (Fe, Ba, Cd), traffic exhaust (P, OC + EC), regional-scale transport (, , V), crustal contributions (Al2O3, Sr, K) and sea spray (Na, Cl). The spatial distribution of the sources was obtained by coupling PCA with wind direction data, which helped identify regional drainage flows as the main source of crustal material. The same analysis showed that the contribution of motorway traffic to PM10 levels is 4-5 microg m-3 higher than that of local traffic. The coupling of PCA-MLRA with wind direction data proved thus to be useful in extracting further information on source contributions and locations. Correct identification and characterisation of PM sources is essential for the design and application of effective abatement strategies.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

Exploring the impact of new particle formation events on PM2.5 pollution during winter in the Yangtze River Delta, China

New particle formation（NPF） events are an increasingly interesting topic in air quality and climate science. In this study, the particle number size distributions, and the frequency of NPF events over Hefei were investigated from November 2018 to February 2019. The proportions of the nucleation mode, Aitken mode, and accumulation mode were 24.59%,53.10%, and 22.30%, respectively, which indicates the presence of abundant ultrafine particles in Hefei. Forty-six NPF events occurred during the obser...     

浙江省丽水市空气质量的健康效应分析

本研究利用2013~2018年丽水空气质量、健康及气象等官方数据，采用半参数广义可加模型分析了丽水市空气质量状况与人群健康效应之间的关系.结果表明：（1）大气污染物可导致人群心血管疾病和呼吸系统疾病死亡率的增加，PM_2.5和O₃对于男性的影响显著高于女性，NO₂和SO₂对于女性的影响显著高于男性，污染物对于65岁以上人口的影响更为明显；（2）O₃对于全人群超额死亡风险的贡献率高达40%~50%，远高于PM_2.5对健康造成的危害，O₃已经成为丽水市最为突出的空气污染物.但是男性和女性有明显差异，O₃对于男性的超额风险贡献率最大，NO₂对于女性的超额风险贡献率最大；（3）丽水市污染物浓度处于剂量-效应关系曲线的低浓度处，单位污染物浓度的变化导致超额死亡率变化较大，降低单位浓度污染物产生的健康效益也更为显著.     

上海崇明岛近三年PM_(2.5)浓度变化特征与气象条件的关系

利用2011年1月~2014年2月上海崇明岛地区颗粒物(PM_(2.5)、PM_(10))的连续监测资料,研究了PM_(2.5)总体分布、季节变化、日变化及浓度频率分布规律,初步分析了逆温、相对湿度、风向风速等气象要素对颗粒物浓度的影响。结果表明:2011~2013年该地区PM_(2.5)平均值分别为24.7,33.6和28.3μg/m~3,均低于PM2.5的年平均浓度限值35μg/m~3,细粒子污染程度较轻。PM_(2.5)浓度日变化幅度不大,呈微弱的单峰型分布,9∶00左右达到一天中的最大值,15∶00左右达到最小值。PM_(2.5)浓度的季节分布特征明显,呈现出冬季春季秋季夏季,一般情况下5月份PM_(2.5)月均浓度值最高,8月份浓度最低。PM_(2.5)日平均浓度有57.9%达到国家空气质量一级标准,有93.4%达到国家空气质量二级标准,超标率为6.6%。对PM_(2.5)与各气象要素进行分析后发现:PM_(2.5)质量浓度在逆温层结稳定、风速小、高湿以及近地面盛行西北到西风这样的静稳天气条件配合高空西北方向上的外来污染物输送,容易造成高浓度的PM_(2.5)污染。     

亚青会期间南京污染气体与气溶胶中水溶性离子的分布特征

使用β射线测尘仪、EMS污染气体监测系统、安德森9级采样器和IC型离子色谱分析仪对2013年8月10~28日南京市亚青会期间PM2.5、污染气体和水溶性离子进行了观测分析.结果表明,在亚青会期间PM2.5、NO2、O3和CO的浓度分别为37.0、19.3、48.1和0.7×103μg·m-3,分别比亚青会前降低了26.0%、42.6%、36.1%和46.1%.亚青会期间,细粒子段主要水溶性离子为Na+、NH+4、Ca2+和SO2-4,占80.6%;粗粒子段主要水溶性离子为Na+、Ca2+、NO-3和SO2-4,占77.9%.Ca2+、Mg2+和NO-3在亚青会期间为双峰型分布,其余离子为三峰型分布;亚青会前和后水溶性离子均为三峰型分布.由NO-3/SO2-4的值判断亚青会前和后南京市SO2和NOx主要来自于移动源,在亚青会期间主要来自固定源.     

PM_(2.5)细颗粒物捕集设备研究应用现状

PM2.5细颗粒物因其粒径小、吸附能力强、环境影响大,同时捕集困难而成为备受世界各国关注的大气环境问题,我国也将PM2.5作为空气质量标准的一项新指标。结合现有的标准和技术条件,对PM2.5细颗粒物有高效捕集效果的新型袋式除尘器、湿式电除尘器、电凝并器、电—袋混合式除尘器,特别是无机膜过滤器的特点、研究应用现状及存在问题进行了概述。     

上海宝山区PM_(2.5)特征研究与源解析研究

利用2011年8月-2012年7月环保局(对照点)和钢研所(工业区)两个监测点的PM2.5的24小时连续监测数据,分析了上海市宝山区大气中PM2.5的浓度时空变化特征。并以四次灰霾事件为例解析了灰霾期间大气颗粒水溶性离子特征,以及灰霾期间PM2.5源特征。PM2.5中水溶性无机离子是以二次离子为主,因此,二次离子的污染水平可反映PM2.5的污染程度,是主要影响灰霾天气产生的物质。灰霾期间大气条件有利于二次离子的大量形成,更进一步加重大气细粒子的污染。而且,宝山地区大气细粒子污染具有受本地流动源和固定源双重排放控制的特征。     

重庆地区区域灰霾观测初步研究

2012年灰霾试点监测结果表明,灰霾日天数有明显减少。细颗粒物(PM2.5)浓度限值增加,使仅因重庆城市地域和气候原因造成部分相对湿度较低,而实际环境空气质量较好的灰霾日排除在外,更客观评价灰霾日发生规律。结合气象条件和颗粒物质量浓度对比情况表明,局域气候条件的变化将促使PM2.5和PM1吸湿增长明显,一定程度上促使粗颗粒物PM10质量浓度增加,局域污染物传输扩散不利,能见度减低,灰霾现象频增。