共查询到20条相似文献,搜索用时 62 毫秒
1.
AERMOD是美国环保局推出的新一代空气质量模式系统,它由AERMET(气象数据预处理器)、AERMAP(地形数据预处理器)和AERMOD(大气扩散模型)3部分组成.结合宁波市北仑区域大气环境影响评价,对该模式系统进行模式验证,并应用于实际预测评价.验证结果表明,在采用适当的模型参数时,该系统预测值与实际监测值具有很好的一致性,SO2、NO2日均最高浓度预测准确率分别达到64.3%和85.7%.最后结合实际预测评价工作,提出AERMOD模式系统在国内环境影响评价工作中的优势及不足. 相似文献
2.
大气环境影响评价是环境影响评价的一项重要内容,而其中最主要的部分就是计算各种大气扩散模式下的地面污染浓度,然后据此结果作出评价.为方便气象资料的整理和大气扩散的计算,因此使用Matlab软件,编制这套大气环境影响评价点源预测模型软件系统. 相似文献
3.
海岸地区热力内边界层(TIBL)对大气污染物扩散具有重要影响。选取杭州湾地区某区域为模拟区,采用一个TIBL高度的简单计算模式模拟模拟区的TIBL高度,将其耦合到空气质量模式AERMOD中,并对AERMOD的相关模块和参数进行了相应的修改,再分别利用原AERMOD和改进后的AERMOD,模拟了不同污染源情景下的大气污染物地面浓度分布。结果表明,在多数情况下,由于TIBL对于大气污染物扩散空间的限制,大气污染物的地面最大浓度有所升高,地面浓度的高值区范围也有所增加,具体影响特征取决于污染源与TIBL的相对高度以及污染源距离海岸的相对位置。 相似文献
4.
工程项目对大气污染影响的定量预测是通过大气扩散模式计算来实现的。本文根据近年实践经验,对大气扩散模式的选用、扩散参数的确定及修正、地面长短期浓度的计算和计算结果的验证等方面作了较为系统的介绍,经供环境影响评价工作者参考。 相似文献
5.
应用灰色系统理论中的重要内容之一———灰色关联分析方法将黑龙江省兴隆生猪屠宰分割综合加工厂新建项目可能对环境造成影响的因子进行环境影响综合评价。研究结果表明 ,该项目的建设使环境质量恶化了 3.14 % ,但仍在环境标准允许范围之内。该方法原理简单 ,计算简便 ,结果可靠 ,是一种很有实用价值的环境影响评价方法。 相似文献
6.
3S(GIS、GPS、RS)技术在发达国家已得到广泛应用,中国政府管理部门也已高度重视,因此在介绍了3S各项技术功能的基础上,进一步阐述了在环境影响评价中的应用,以及3S集成技术在中国当前环境影响评价中的应用前景。 相似文献
7.
应用灰色系统理论中的重要内容之一——灰色关联分析方法将黑龙江省兴隆生猪屠宰分割综合加工厂新建项目可能对环境造成影响的因子进行环境影响综合评价。研究结果表明,该项目的建设使环境质量恶化了3.14%,但仍在环境标准允许范围之内。该方法原理简单,计算简便,结果可靠,是一种很有实用价值的环境影响评价方法。 相似文献
8.
在新时期,环境保护工作的发展面临着新的机遇和挑战。环境监测贯穿于整个环境影响评价体系之中,即环境影响评价中的评价初期、建设期、运行期以及后评价期,均需环境监测数据来支撑,因此,环境监测是环境影响评价的技术基础,同时还具有较强的监督功能。 相似文献
9.
阐述了循环经济的内涵、特点,分析了循环经济理念导人环境影响评价中应注意的几个环节,探讨了区域生态产业链、物质流分析法、循环经济指标等在区域规划环境影响评价中的应用,并提出了相关的建议及措施。 相似文献
10.
循环经济是建设生态文明的有效途径,规划环境影响评价是减少决策失误、保证科学发展的基本手段.把循环经济理念融入到规划环境影响评价中,能有效地推进循环经济的实施.结合规划环境影响评价的实践,分析了规划环境影响评价与循环经济的关系,讨论了将循环经济理论和方法体系纳入区域规划环境影响评价体系的途径.结合天津先进制造业产业区总体规划环境影响评价,从技术思路的完善、规划环境影响评价全过程中循环经济理念的落实等进行了细致的分析. 相似文献
11.
The European critical levels (CLs) to protect vegetation are expressed as an accumulative exposure over a threshold of 40 ppb (nl l(-1)). In view of the fact that these chamber-derived CLs are based on ozone (O(3)) concentrations at the top of the canopy the correct application to ambient conditions presupposes the application of Soil-Vegetation-Atmosphere-Transfer (SVAT) models for quantifying trace gas exchange between phytosphere and atmosphere. Especially in the context of establishing control strategies based on flux-oriented dose-response relationships, O(3) flux measurements and O(3) exchange simulations are needed for representative ecosystems. During the last decades several micrometeorological methods for quantifying energy and trace gas exchange were developed, as well as models for the simulation of the exchange of trace gases between phytosphere and atmosphere near the ground. This paper is a synthesis of observational and modeling techniques which discusses measurement methods, assumptions, and limitations and current modeling approaches. Because stomatal resistance for trace gas exchange is parameterized as a function of water vapor or carbon dioxide (CO(2)) exchange, the most important micrometeorological techniques especially for quantifying O(3), water vapor and CO(2) flux densities are discussed. A comparison of simulated and measured O(3) flux densities shows good agreement in the mean. 相似文献
12.
In this study the performance of the American Meteorological Society and U.S. Environmental Protection Agency Regulatory Model (AERMOD), a Gaussian plume model, is compared in five test cases with the German Dispersion Model according to the Technical Instructions on Air Quality Control (Ausbreitungsmodell gem?beta der Technischen Anleitung zur Reinhaltung der Luft) (AUSTAL2000), a Lagrangian model. The test cases include different source types, rural and urban conditions, flat and complex terrain. The predicted concentrations are analyzed and compared with field data. For evaluation, quantile-quantile plots were used. Further, a performance measure is applied that refers to the upper end of concentration levels because this is the concentration range of utmost importance and interest for regulatory purposes. AERMOD generally predicted concentrations closer to the field observations. AERMOD and AUSTAL2000 performed considerably better when they included the emitting power plant building, indicating that the downwash effect near a source is an important factor. Although AERMOD handled mountainous terrain well, AUSTAL2000 significantly underestimated the concentrations under these conditions. In the urban test case AUSTAL2000 did not perform satisfactorily. This may be because AUSTAL2000, in contrast to AERMOD, does not use any algorithm for nightly turbulence as caused by the urban heat island effect. Both models performed acceptable for a nonbuoyant volume source. AUSTAL2000 had difficulties in stable conditions, resulting in severe underpredictions. This analysis indicates that AERMOD is the stronger model compared with AUSTAL2000 in cases with complex and urban terrain. The reasons for that seem to be AUSTAL2000's simplification of the meteorological input parameters and imprecision because of rounding errors. 相似文献
13.
ABSTRACT In this study the performance of the American Meteorological Society and U.S. Environmental Protection Agency Regulatory Model (AERMOD), a Gaussian plume model, is compared in five test cases with the German Dispersion Model according to the Technical Instructions on Air Quality Control (Ausbreitungsmodell gemäβ der Technischen Anleitung zur Reinhaltung der Luft) (AUSTAL2000), a Lagrangian model. The test cases include different source types, rural and urban conditions, flat and complex terrain. The predicted concentrations are analyzed and compared with field data. For evaluation, quantile-quantile plots were used. Further, a performance measure is applied that refers to the upper end of concentration levels because this is the concentration range of utmost importance and interest for regulatory purposes. AERMOD generally predicted concentrations closer to the field observations. AERMOD and AUSTAL2000 performed considerably better when they included the emitting power plant building, indicating that the downwash effect near a source is an important factor. Although AERMOD handled mountainous terrain well, AUSTAL2000 significantly underestimated the concentrations under these conditions. In the urban test case AUSTAL2000 did not perform satisfactorily. This may be because AUSTAL2000, in contrast to AERMOD, does not use any algorithm for nightly turbulence as caused by the urban heat island effect. Both models performed acceptable for a nonbuoyant volume source. AUSTAL2000 had difficulties in stable conditions, resulting in severe underpredictions. This analysis indicates that AERMOD is the stronger model compared with AUSTAL2000 in cases with complex and urban terrain. The reasons for that seem to be AUSTAL2000's simplification of the meteorological input parameters and imprecision because of rounding errors. IMPLICATIONS This study contributes to the understanding of dispersion modeling and demonstrates the advantage of detailed meteorological data. It also helps air quality regulators and planners to identify the most appropriate model to use. It is indicated that AERMOD is more suitable for air quality planning and regulation, when all required meteorological information is available, because its predictions are mostly closer to field observations. Furthermore AUSTAL2000 predicted concentrations that showed a narrow range and triggered far less impacts from the source. 相似文献
14.
State space models for tropospheric urban ozone prediction are introduced and compared with linear regression models. The
linear and non-linear state space models make accurate short-term predictions of the ozone dynamics. The average prediction
error one hour in advance is 7 μg/m 3 and increases logarithmically with time until it reaches 26 μg/m 3 after 30 days. For a given sequence of solar radiation inputs, predictions converge exponentially with a time scale of 8
hours, so that the model is insensitive to perturbations of more than 150 μg/m 3 O 3. The slow increase of the prediction error in addition to the uniqueness of the prediction are encouraging for applications
of state space models in forecasting ozone levels when coupled with a model that predicts total radiation. Since a radiation
prediction model will be more accurate during cloud-free conditions, in addition to the fact that the state space models perform
better during the summer months, state space models are suitable for applications in sunny environments. 相似文献
15.
Air quality models are typically used to predict the fate and transport of air emissions from industrial sources to comply with federal and state regulatory requirements and environmental standards, as well as to determine pollution control requirements. For many years, the U.S. Environmental Protection Agency (EPA) widely used the Industrial Source Complex (ISC) model because of its broad applicability to multiple source types. Recently, EPA adopted a new rule that replaces ISC with AERMOD, a state-of-the-practice air dispersion model, in many air quality impact assessments. This study compared the two models as well as their enhanced versions that incorporate the Plume Rise Model Enhancements (PRIME) algorithm. PRIME takes into account the effects of building downwash on plume dispersion. The comparison used actual point, area, and volume sources located on two separate facilities in conjunction with site-specific terrain and meteorological data. The modeled maximum total period average ground-level air concentrations were used to calculate potential health effects for human receptors. The results show that the switch from ISC to AERMOD and the incorporation of the PRIME algorithm tend to generate lower concentration estimates at the point of maximum ground-level concentration. However, the magnitude of difference varies from insignificant to significant depending on the types of the sources and the site-specific conditions. The differences in human health effects, predicted using results from the two models, mirror the concentrations predicted by the models. 相似文献
16.
The only documentation on the building downwash algorithm in AERMOD (American Meteorological Society/U.S. Environmental Protection Agency Regulatory Model), referred to as PRIME (Plume Rise Model Enhancements), is found in the 2000 A&WMA journal article by Schulman, Strimaitis and Scire. Recent field and wind tunnel studies have shown that AERMOD can overpredict concentrations by factors of 2 to 8 for certain building configurations. While a wind tunnel equivalent building dimension study (EBD) can be conducted to approximately correct the overprediction bias, past field and wind tunnel studies indicate that there are notable flaws in the PRIME building downwash theory. A detailed review of the theory supported by CFD (Computational Fluid Dynamics) and wind tunnel simulations of flow over simple rectangular buildings revealed the following serious theoretical flaws: enhanced turbulence in the building wake starting at the wrong longitudinal location; constant enhanced turbulence extending up to the wake height; constant initial enhanced turbulence in the building wake (does not vary with roughness or stability); discontinuities in the streamline calculations; and no method to account for streamlined or porous structures. Implications: This paper documents theoretical and other problems in PRIME along with CFD simulations and wind tunnel observations that support these findings. Although AERMOD/PRIME may provide accurate and unbiased estimates (within a factor of 2) for some building configurations, a major review and update is needed so that accurate estimates can be obtained for other building configurations where significant overpredictions or underpredictions are common due to downwash effects. This will ensure that regulatory evaluations subject to dispersion modeling requirements can be based on an accurate model. Thus, it is imperative that the downwash theory in PRIME is corrected to improve model performance and ensure that the model better represents reality. 相似文献
17.
Dimethyl sulfide (DMS) and atmospheric aerosols were sampled simultaneously over the Atlantic Ocean in the vicinity of Bermuda using the NOAA King Air research aircraft. Total and fine (50% cutoff at 2 μm diameter) aerosol fractions were sampled using two independent systems. The average nonsea-salt (nss)SO 42− concentrations were 1.9 and 1.0 μg m −3 (as SO 42−) for the total and the fine fractions in the boundary layer (BL) and 0.53 and 0.27 μg m −3 in the free troposphere (FT). Non-sea-salt SO 42− in the two aerosol fractions were highly correlated ( r = 0.90), however a smaller percentage (55%) was found in the fine aerosol near Bermuda relative to that (90%) near the North American continent. The BL SO 42− concentrations measured in this study were higher than those measured by others at remote marine locations despite the fact that the 7-day air mass back trajectories indicated little or no continental contact at altitudes of 700 mb and below; the trajectories were over subtropical oceanic areas that are expected to be rich in DMS. DMS concentrations were higher near the ocean surface and decreased with increasing altitude within the BL; the average DMS concentration was 0.13 μg m −3. Trace levels of DMS were also measured in the FT (0.01 μg m −3). Computer simultation of the oxidation and removal of DMS in the marine atmosphere suggests that <50% of the SO 42− observed could be related to the natural S cycle. 相似文献
18.
全球气候的变化激发了人们对现有的和潜在的碳汇的研究兴趣.结合上海市和东京市的基本状况,分析了上海市和东京市主要的陆地碳汇类型,根据相关文献研究和当地的基本情况确定碳汇参数,研究了不同陆地碳汇类型的碳汇量,进而估算出陆地总碳汇量.在此基础上,从不同的角度对比分析了2个城市的陆地碳汇能力,并提出了加强湿地保护工作、加强园林绿化建设工作、保护耕地等增强上海市陆地碳汇能力的对策. 相似文献
19.
分析了我国现阶段环境影响评价中存在的问题和不足,提出了对策和建议。 相似文献
|