郑州市大气环境中醛酮类化合物污染状况初探

在郑州市交通密集区、工业区、居民文化区等不同功能区设置监测点位,分春季、夏季、冬季不同季节对郑州市大气环境中15种醛酮类的污染状况进行初步研究。结果表明,郑州市大气环境中醛酮类主要污染物为甲醛、乙醛和丙酮;醛酮类污染物含量在不同季节的变化趋势是夏季春季冬季;功能区的变化趋势是交通密集区居民区;污染物主要来源于大气中有机物的光化学反应,甲醛与乙醛、甲醛与丙酮有较好的相关性。     

郑州市环境空气中多环芳烃污染状况及变化规律的研究

对郑州市2004年环境空气中多环芳烃的污染状况及变化规律进行了初步研究,结果表明,郑州市环境空气中15种优控PAHs的浓度范围为未检出-698ng/m3,强致癌性物质苯并(a)芘的检出率为100%,其浓度范围为1.56～136ng/m3.PAHs类物质在不同季节的变化趋势为冬季＞秋季＞春季＞夏季;在不同功能区变化趋势为工业区＞混合区＞交通密集区＞文化区＞对照区.     

南京市环境空气中挥发性有机物的组成与特点

参照美国EPATO17的方法研究南京市不同功能区(交通区、商业旅游区、居住区、工业区和清洁对照点)环境空气中挥发性有机物(VOCs)在一年四季中的组成及浓度水平。共检出189种挥发性有机物,并随气温下降而减少;苯系物稳定存在于各功能区,浓度秋季最高。交通区污染最严重。     

郑州市环境空气中挥发性有机物的组成及分布特点

初步探查研究了郑州市不同功能区环境空气中挥发性有机物(VOCs)的种类组成及TVOC和苯系物浓度分布特点,共检测出221种VOCs.交通密集区VOCs污染较重,汽车尾气是目前VOCs主要来源.     

盐城市空气微生物调查与评价

为了解盐城市空气微生物污染状况,于2009—2013年在盐城市布设了4个城市主要功能区点位和1个市郊清洁参照点,采用自然沉降法采集空气中细菌和马丁霉菌样品进行分析。结果表明,盐城市空气中细菌数量最多的为交通区,其次依次为文教区、工业区、居民区,清洁参照点最少;马丁霉菌数量最多的是交通区,其次依次为工业区、居民区、文教区,清洁参照点最少。盐城市空气微生物污染级别除交通区外,其他功能区均处于较清洁或轻微污染,污染程度呈逐年波动下降趋势。     

鞍山大气中有机氯农药的污染特征研究

布设鞍钢工业区6个点位,周边2个点位,居民区2个点位和千山对照点等11个点位,分别在采暖期和非采暖期测定大气中有机氯农药的含量,掌握了鞍山市大气中有机氯农药空间和时间变化趋势。全年有机氯农药各组分和ΣOPC浓度最高的功能区均为工业区周边,最低的功能区是千山对照点,六六六、滴滴涕和ΣOPC浓度变化趋势为工业区周边工业区居住区千山对照点,全市各功能区采暖期有机氯农药各组分和ΣOPC总浓度均高于非采暖期。     

沈阳市环境空气中挥发性有机物污染特征及来源解析

基于2019年沈阳市4个不同功能区挥发性有机物(VOCs)小时分辨率的在线监测数据,分析了环境空气中VOCs的污染特征及来源。结果表明,观测期间沈阳市环境空气中VOCs日平均体积分数为(31.5±13.3)×10~(-9),4个功能区VOCs体积分数均呈现出冬季明显大于夏季的特征;工业区环境空气中VOCs体积分数明显高于其他功能区。商业交通居民混合区、文化居民混合区、郊区VOCs体积分数呈现明显双峰结构,工业区双峰结构不明显。工业区VOCs以新鲜排放为主,而其他3个区域为老化气团的传输。工业区春、夏季环境空气中VOCs来源包括燃料挥发源(26.90%)、溶剂与涂料源(17.69%)、燃烧源(16.40%)、化工源(15.69%)、交通源(7.57%)和炼油炼焦源(4.15%)。秋、冬季VOCs的来源包括燃烧源(30.77%)、溶剂与涂料源(20.26%)、燃料挥发源(18.79%)、化工源(11.54%)、炼油炼焦源(9.34%)和交通源(5.51%)。     

深圳特区不同功能区大气微生物污染调查

采用平皿沉降法,测定了深圳特区不同功能区37个监测点人群呼吸带内的大气细菌数和真菌数,结果表明,特区内不同功能区大气微生物的浓度各异,其中市区商业交通混杂区的大气细菌污染最重,其次是工业区和交通干线,文教区和居民区、旅游区大气细菌含量最低。绿化情况良好的文教区、居民区、果园的真菌含量高于工业区和交通干线。以大气细菌含量为指标评价了各测点的空气质量,参与评价的37个测点中,清洁点占56.8%,普通点占29.7%,属界限空气的测点占8.1%,5.4%的测点空气已出现轻度污染。大气细菌的日浓度变化规律为:早上(6:30)、晚上(18:30)较高,上午(10:30)、下午(14:30)较低。     

杭州秋季大气VOCs变化特征及化学反应活性研究

2017年9月1日至11月30日采用Syntech Spectras GC955在线气相色谱仪对杭州市不同功能区大气环境中的挥发性有机化合物(VOCs)进行了在线连续监测,分析了不同功能区VOCs及各组分的体积分数、日变化规律及大气化学反应活性。结果显示,下沙周边工业区总VOCs浓度整体高于朝晖周边居民区,其中夜间更为显著。烷烃和芳香烃浓度在夜间时段工业区较居民区高得更为明显,其中芳香烃组分表现尤为突出,2个功能区烯烃体积分数相差不大。杭州市主要VOCs体积分数总体上在国内处于中间水平。不同功能区烷烃和芳香烃均呈现夜间浓度高于白天的日变化特征,居民区各VOCs组分日变化基本呈现双峰结构,工业区烷烃和芳香烃体积分数日变化呈现单峰结构,烯烃体积分数没有明显的日变化特征。不同功能区中芳香烃对臭氧生成潜势贡献最大,烯烃次之,烷烃贡献最小。下沙周边工业区大气化学活性(尤其是芳香烃组分)较朝晖周边居民区强。同种VOCs物质在不同功能区对臭氧生成潜势的贡献大小不同,但关键贡献物质均为低碳烷烃、低碳烯烃及苯系物。     

齐齐哈尔市不同功能区大气微生物污染研究

齐齐哈尔市不同功能区大气微生物污染研究周晏敏，韩梅，陈震宇（黑龙江齐齐哈尔市环境监测站，１６１００５）１．研究方法１．ｌ布点：选设５个采样点，即一百（齐市商业中心，人口稠密区）。二厂（齐齐哈尔第二机床厂，工业区），轻工学院（文化区），建工小区（楼房居...     

Soil Lead and Other Metal Levels in Industrial, Residential and Nature Reserve Areas in Singapore

The use of pressure feedback microwave digestion technique has permitted rapid and efficient digestion of soil and sediment samples. The evaluation of different acid mixtures to digest soil samples were studied by mixed-level orthogonal array design. The selected acid mixture of HCl-HNO3-HF was employed in the survey of Pb, Zn, Cu, Cr and Mn in soil samples. Surface soil samples were collected from industrial, residential and nature reserve areas in Singapore. The five metal concentrations were determined by flame atomic absorption spectrometry and graphite furnace atomic absorption spectrometry. The lead and other metal contents in NBS SRM 1645, NIES CRM No. 2 and NRCC BCSS-1 sediment standard references were determined concurrently with the survey samples. Five measured metal loading on the surface soils was in the order: industrial area > residential area > nature reserve area. The trace metal concentrations in surface soil from areas of heavy traffic are higher than those from residential areas. The main sources of trace metal pollution are vehicular exhaust and industrial activities.     

常州市秋季大气PM2.5中多环芳烃污染水平及来源

为了研究常州市秋季大气PM2.5中多环芳烃的污染水平及其来源,在常州市布设了6个采样点,分别代表交通干道区、商业混合区、居民文教区、远郊区、工业区和对照点,于2013年10月进行大气PM2.5的采样,采用微波萃取-高效液相色谱法测定其中16种USEPA优控多环芳烃的浓度值,并分别通过比值法和因子分析法判断其主要来源。结果表明,常州市秋季大气PM2.5中多环芳烃的主要来源为煤燃烧和机动车排放。     

A comparative study of noise levels in some residential,industrial and commercial areas of Delhi

The measurements of noise levels in residential, industrial and commercial areas in the capital city of India, Delhi, were carried out in the month of March and April, 1992. Six sites in residential areas, four in industrial areas and nine in commercial areas were chosen, which were situated in different parts of Delhi. The results of statistical analysis of sound pressure levels show that commercial areas have the highest noise levels followed by industrial and residential areas. Spectral distribution of noise at octave band frequencies have also been presented for the above mentioned areas.     

Distribution,sources, and ecological risk assessment of SVOCs in surface sediments from Guan River Estuary,China

The contamination of semi-volatile organic compounds (SVOCs) in the surface sediments of the Guan River Estuary, China was fully investigated. Total concentrations of 56 species of SVOCs ranged from 132 to 274 ng/g with an average of 186 ng/g (dry weight). Polycyclic aromatic hydrocarbon (PAH) concentrations were positively correlated with clay content and negatively correlated with sediment grain size. Source identification indicated that PAHs originated mainly from pyrolytic sources. However, intense ship traffic in the estuary may provide sources of petrogenic PAHs. Organochlorine pesticides (OCPs) mainly originated from direct input of dichlorodiphenyltrichloroethanes (DDTs) during some industrial processes. The SVOC concentrations were also compared with International Sediments Quality Guidelines and Sediments Quality Criteria, and the results indicated that negative biological impacts may originate from high concentrations of FLO, p,p′-DDE, and total DDTs.     

Analysing and mapping spatial and temporal dynamics of urban traffic noise pollution: a case study in Kahramanmaraş, Turkey

This study aimed at quantifying noise pollution from urban traffic in the city of Kahramanmara?, Turkey. A total of 114 measurements for the equivalent noise level (L _Aeq) were made at 38 urban locations classified as “residential areas”, “residential and commercial areas” and “industrial areas” according to the national regulations, during morning, mid-day and evening hours. Our findings tabulated and mapped revealed that mean noise level in “residential and commercial areas” was highest relative to the other land-use types. Minimum and maximum values of noise pollution were recorded during the mid-day and evening hours, regardless of the land-use types. Noise limit values were exceeded at two locations only out of 38 based on the national regulation criteria and at over half of the locations based on the international criteria.     

基于多源大数据可视化的城市居民区绿地土壤环境监测点位布设及采样研究

为科学合理的监测城市居民区绿地土壤环境状况,对居民区绿地土壤监测点位布设和采样的方法进行研究,包括代表性居民区的选取、监测点采样位置的确定、点位数量的确定等。通过多源大数据可视化手段选取某城市代表性的居民区,对其居民区内绿地土壤重金属(镉、汞、砷、铅、铜、铬、锌和镍)进行监测。结果表明:多源大数据的应用对城市土壤监测布点具有积极作用和优势;不同建筑年代的居民区土壤中重金属含量存在一定差异,为全面监测居民区土壤环境状况应选取不同建筑年代的居民区作为监测对象;不同采样位置对居民区土壤样品中重金属含量无明显影响,优先于居民区内面积占比较大的绿地采样;同一居民区内不同监测点位样品存在差异性,每个居民区内至少布设3~4个监测点位可代表该居民区土壤环境状况。     

A comparative study of noise pollution levels in some selected areas in Ilorin Metropolis, Nigeria

The noise pollution is a major problem for the quality of life in urban areas. This study was conducted to compare the noise pollution levels at busy roads/road junctions, passengers loading parks, commercial, industrial and residential areas in Ilorin metropolis. A total number of 47-locations were selected within the metropolis. Statistical analysis shows significant difference (P < 0.05) in noise pollution levels between industrial areas and low density residential areas, industrial areas and high density areas, industrial areas and passengers loading parks, industrial areas and commercial areas, busy roads/road junctions and low density areas, passengers loading parks and commercial areas and commercial areas and low density areas. There is no significant difference (P > 0.05) in noise pollution levels between industrial areas and busy roads/road junctions, busy roads/road junctions and high density areas, busy roads/road junctions and passengers loading parks, busy roads/road junctions and commercial areas, passengers loading parks and high density areas, passengers loading parks and commercial areas and commercial areas and high density areas. The results show that Industrial areas have the highest noise pollution levels (110.2 dB(A)) followed by busy roads/Road junctions (91.5 dB(A)), Passengers loading parks (87.8 dB(A)) and Commercial areas (84.4 dB(A)). The noise pollution levels in Ilorin metropolis exceeded the recommended level by WHO at 34 of 47 measuring points. It can be concluded that the city is environmentally noise polluted and road traffic and industrial machineries are the major sources of it. Noting the noise emission standards, technical control measures, planning and promoting the citizens awareness about the high noise risk may help to relieve the noise problem in the metropolis.     

西安市表层土壤中邻苯二甲酸酯(PAEs)含量与构成

通过在西安市三环内6个功能区布设62个采样点,采样分析其表层土壤中邻苯二甲酸酯(PAEs)质量比及其构成特征。结果表明,西安市表层土壤中DMP、DEP、BBP、DnBP、DEHP和DnOP平均值分别为0.188 mg/kg、0.187 mg/kg、0.091 mg/kg、4.174 mg/kg、6.122 mg/kg和0.188 mg/kg,6种PAEs总质量比(∑6PAEs)范围为1.54 mg/kg^153.17 mg/kg,平均值为10.95 mg/kg。6个功能区∑6PAEs从高到低为交通区>工业区>混合区>公园>文教区>住宅区。与其他城市表层土壤中PAEs值比较发现,DMP处于高水平,DEP、DnBP、DEHP和∑6 PAEs处于较高水平,BBP和DnOP处于中等水平。     

Assessment of elemental concentrations in the urban air (case study: Tehran city)

Tehran is one of the megacities of the world with a population of over eight million. Its air is highly polluted mainly due to the suspended particulate matters, which encompasses a wide spectrum of chemical elements. These elements based on their type, size, and impact on the life cycle have various environmental and heath risks. In this research, the neutron activation method is used to determine the concentration levels of Al, Ba, Fe, Mg, and V in the urban air. Thus, two districts of Tehran with different characteristics are selected. District 21 includes much of the industries located in Tehran metropolitan and is considered as an industrial area. In contrast, district 22 lacks any significant industrial activity. It is a newly established and expanding district adjacent to district 21 with a great deal of constructional activities. For the measurement of the suspended particulate matters in the air, the various sections of the aforesaid districts with industrial, residential, heavily congested traffic, residential/commercial, residential/heavily congested traffic, and residential/industrial classifications were identified. Subsequently, 24 sampling stations were selected. The sampling of the suspended particulate matters was conducted with the aid of a high volume pump containing 125 mm cellulose filters in two different time intervals. After completion of the sampling process, the samples were prepared and sent to the research reactor of the Iran Nuclear Energy Organization for Neutron Activation. During the next steps, the radiations emitted from the samples were registered, the radiation curves were plotted, and the amounts of the trace elements were determined. As a result, the average concentration levels of Al, Ba, Fe, Mg, and V were identified to be 3.301140, 2.273658 × 10, 4.0681696 × 10^???1, 3.5525475 × 10^???1, and 3.04075 × 10^???2 μg/m³, respectively. Moreover, the emission sources of the aforesaid elements into the air were identified. The concentration levels of these elements in the industrial and heavily congested traffic sections were higher. Finally, it was concluded that the statistical analysis of these elements presents a meaningful correlation among them.