共查询到10条相似文献,搜索用时 102 毫秒
1.
基于道路交通噪声990 h监测数据,对英国CRTN模型中源强计算模型在中国的适用性进行了验证。试验结果表明,理论计算与实测结果之间平均仅相差0.57 dB(A),CRTN源强预测模型在中国可以可靠地预测道路交通噪声。 相似文献
2.
Attitudinal response towards road traffic noise in the industrial town of Asansol, India 总被引:1,自引:0,他引:1
Banerjee D Chakraborty SK Bhattacharyya S Gangopadhyay A 《Environmental monitoring and assessment》2009,151(1-4):37-44
The major objective of the investigation was to evaluate the road traffic noise and its likely impacts on the local community of Asansol city (West Bengal, India) by monitoring and modeling. The attitudinal response of local population due to existing vehicular noise is presented in the paper. Noise and Attitudinal Survey was conducted at 25 locations. A total of 869 individuals were surveyed. The relationship between traffic noise levels and annoyance was studied using correlation, linear and multiple linear regressions analysis. The average L(dn) value was 73.28 +/- 8.51 dB(A) (55.1-87.3); The Traffic Noise Index (TNI) was 80.62 +/- 15.88 dB(A) (49.4-115.8). The mean value of percent of population Highly Annoyed (%HA) due to road traffic noise was 26.50 +/- 3.37 (19.44-33.2), whereas the mean dissatisfaction score (MDS) was 2.96 +/- 0.90 (1.04-4.45). Annoyance modeling was also performed based on field data. It can be said that Noise values gives desirable annoyance predicting values in comparison to vehicular data. 相似文献
3.
The objective of this study is to develop an empirical traffic noise prediction model under interrupted traffic flow conditions
using two analytical the approaches, the first being the acceleration lane approach and second being the deceleration approach.
The urban road network of Bangalore city has been selected as the study area. Sixteen locations are chosen in major traffic
junctions of the study area. The traffic noise data collected from the study locations were analyzed separately for both acceleration
and deceleration lanes when vehicles leave an intersection on a green traffic light and come to a stop on red traffic light.
Based on the study, a regression noise prediction model has been developed for both acceleration and deceleration lanes. 相似文献
4.
Kazi TG Jalbani N Arain MB Jamali MK Afridi HI Shah AQ 《Environmental monitoring and assessment》2009,158(1-4):155-167
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. 相似文献
5.
6.
7.
Roads may act as barriers, negatively influencing the movement of animals, thereby causing disruption in landscapes. Roads cause habitat loss and fragmentation not only through their physical occupation, but also through traffic noise. The aim of this study is to provide a method to quantify the habitat degradation including habitat loss and fragmentation due to road traffic noise and to compare it with those of road land-take. Two types of fragmentation effects are determined: structural fragmentation (based on road land-take only), and functional fragmentation (noise effect zone fragmentation, buffer using a threshold of 40 dB). Noise propagation for roads with a traffic volume of more than 1000 vehicles per day was simulated by Calculation of Road Traffic Noise (CRTN) model. Habitat loss and fragmentation through land-take and noise effect zone were calculated and compared in Zagros Mountains in western Iran. The study area is characterized by three main habitat types (oak forest, scattered woodland and temperate grassland) which host endangered and protected wildlife species. Due to topographic conditions, land cover type, and the traffic volume in the region, the noise effect zone ranged from 50 to 2000 m which covers 18.3% (i.e. 516,929.95 ha) of the total study area. The results showed that the habitat loss due to noise effect zone is dramatically higher than that due to road land-take only (35% versus 1.04% of the total area). Temperate grasslands lost the highest proportion of the original area by both land-take and noise effect zone, but most area was lost in scattered woodland as compared to the other two habitat types. The results showed that considering the noise effect zone for habitat fragmentation resulted in an increase of 25.8% of the area affected (316,810 ha) as compared to using the land-take only (555,874 ha vs. 239,064 ha, respectively). The results revealed that the degree of habitat fragmentation is increasing by considering the noise effect zone. We conclude that, although the roads are breaking apart the patches by land-take, road noise not only dissects habitat patches but takes much larger proportions of or even functionally eliminates entire patches. 相似文献
8.
Olayinka S. Oyedepo Abdullahi A. Saadu 《Environmental monitoring and assessment》2010,160(1-4):563-577
Evaluation and analysis of noise pollution levels have been carried out to determine the level of noise and its sources in Ilorin metropolis. Noise measurements have been done in the morning, at noon, in the evening, and at night to determine noise pollution all over the city. The selected areas of study are commercial centers, road junctions/busy roads, passenger loading parks, and high-density and low-density residential areas. The road junctions had the highest noise pollution levels, followed by commercial centers. The results of this study show that the noise levels in Ilorin metropolis exceeded allowed values at 30 of 42 measurements points. There is a significant difference (P?<?0.05) in the noise pollution levels and traffic noise index in all the locations. From the measured noise values, a map of noise pollution was developed for Ilorin. Many solutions proposed for noise abatement in the city are set out. 相似文献
9.
Can A Van Renterghem T Rademaker M Dauwe S Thomas P De Baets B Botteldooren D 《Journal of environmental monitoring : JEM》2011,13(10):2710-2719
Requirements for static (prediction of L(den) and diurnal averaged noise pattern) and dynamic (prediction of 15 min and 60 min evolution of L(Aeq) and statistical levels L(A90,)L(A50) and L(A10)) noise level monitoring are investigated in this paper. Noise levels are measured for 72 consecutive days at 5 neighboring streets in an inner-city noise measurement network in Gent, Flanders, Belgium. We present a method to make predictions based on a fixed monitoring station, combined with short-term sampling at temporary stations. It is shown that relying on a fixed station improves the estimation of L(den) at other locations, and allows for the reduction of the number of samples needed and their duration; L(den) is estimated with an error that does not exceed 1.5 dB(A) to 3.4 dB(A) according to the location, for 90% of the 3 × 15 min samples. Also the diurnal averaged noise pattern can be estimated with a good accuracy in this way. It was shown that there is an optimal location for the fixed station which can be found by short-term measurements only. Short-term level predictions were shown to be more difficult; 7 day samples were needed to build models able to estimate the evolution of L(Aeq,60min) with a RMSE ranging between 1.4 dB(A) and 3.7 dB(A). These higher values can be explained by the very pronounced short-term variations appearing in typical streets, which are not correlated between locations. On the other hand, moderately accurate predictions can be achieved, even based on short-term sampling (a 3 × 15 minute sampling duration seems to be sufficient for many of the accuracy goals set related to static and dynamic monitoring). Finally, the method proposed also allows for the prediction of the evolution of statistical indicators. 相似文献