机动车污染排放模型研究综述

过去几十年,为了掌握机动车污染排放的规律和特征,向决策者提供科学有效的机动车污染控制措施,研究者们致力于研究机动车污染物排放的物化原理和影响机动车污染的主要因素,并据此建立多种尺度的机动车排放模型,以模拟城市区域或者街道的污染物排放.为了分析机动车的瞬态排放特征,目前的机动车排放模型研究正逐渐从宏观向微观发展,排放测试方法注重获取逐秒的排放数据,排放模型模拟的时间尺度和空间尺度逐步趋向微观.此外,机动车模型研究正趋向与交通模型进行耦合,从而揭示机动车在实际道路交通流中的排放特征.从机动车排放的主要影响因素、机动车排放测试、机动车排放因子模型及机动车排放清单等4个方面综述了国内外机动车排放研究现状和发展动向,对比并评价各种机动车排放模型方法的优缺点和适用范围,对我国的机动车排放模型发展方向进行了展望.     

室内环境中挥发性有机物释放过程的数学模型

根据组成结构,将室内环境中释放挥发性有机物(VOCs)的建筑装饰材料划分为单层干材料、单层湿材料、多层组合材料等类型,总结了这三种材料的VOCs释放特征、传输过程和数学模型研究现状,分析了模型的特点和适用范围,指出了模型研究发展的趋势,对应用中模型的选择提出了指导性建议.     

Evaluation of three regional air quality models

This paper summarizes the results of a thorough assessment of existing regional air quality models. Forty-two candidate models were reviewed and three repsesentative models were selected for rigorous and comprehensive assessment. The underlying scientific theories used in the models were evaluated, revealing many limitations. For example, the techniques used in the preparation of meteorological fields that drive the models give insufficient consideration to the physical basis of the relevant atmospheric processes. The primary operational evaluation of each of the models was performed by comparing calculated values with observations from the EPRI Sulfate Regional Experiment (SURE). Both short-term (6-h averages) and long-term (annual averages) comparisons reveal poor correlations for both SO₂ and SO²⁻₄ for the three models evaluated ranging from 0.05 to 0.32 for 3- to 6-h SO₂ concentration to 0.03 to 0.59 for 24-4 and monthly averages; in some cases, the correlations are negative. The results also show that calculated concentrations are generally characterized by high biases for 3- to 6-h concentration predictions. Biases tend to be somewhat smaller for monthly averages. All three models underpredicted wet deposition with average normalized residuals of approximately 0.2 for ENAMAP-2, and 0.5 for RTM-II and ACID.     

Optimizing emission inventory for chemical transport models by using genetic algorithm

Air pollutant emission inventory is an important input parameter for chemical transport models (CTMs). Since great uncertainties exist in the emission inventory, further improvements and refinements are required. In this paper, genetic algorithm (GA), a global search and optimization method, was applied to optimize the emission inventory for the Models-3/Community Multiscale Air Quality (CMAQ) model. An emission optimizing system based on GA was developed and embedded to the CMAQ through the design of several core modules, which implemented the basic functions such as emission adjusting, GA population initializing, CMAQ results evaluating and GA operating. Hypothetical and real-data experiments were respectively performed to examine the validity of GA for emission calibrating. GA showed good performance in both experiments and was always able to find the global minimum. The emission optimizing system was then used to calibrate seasonal PM₁₀ emission inventories of Beijing. Results revealed that PM₁₀ emission in Beijing was underestimated in 2002, an average of 62.74% higher adjustment factor should be imposed on the original emission in target months of different seasons. With the calibrated emission inventories, CMAQ model errors were decreased by 6.46% on average in different seasons. It was concluded that GA was a promising search technique in calibrating emission inputs for CTMs.     

Comparison of regional and global land cover products and the implications for biogenic emission modeling

Accurate estimates of biogenic emissions are required for air quality models that support the development of air quality management plans and attainment demonstrations. Land cover characterization is an essential driving input for most biogenic emissions models. This work contrasted the global Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product against a regional land cover product developed for the Texas Commissions on Environmental Quality (TCEQ) over four climate regions in eastern Texas, where biogenic emissions comprise a large fraction of the total inventory of volatile organic compounds (VOCs) and land cover is highly diverse. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) was utilized to investigate the influences of land cover characterization on modeled isoprene and monoterpene emissions through changes in the standard emission potential and emission activity factor, both separately and simultaneously. In Central Texas, forest coverage was significantly lower in the MODIS land cover product relative to the TCEQ data, which resulted in substantially lower estimates of isoprene and monoterpene emissions by as much as 90%. Differences in predicted isoprene and monoterpene emissions associated with variability in land cover characterization were primarily caused by differences in the standard emission potential, which is dependent on plant functional type. Photochemical modeling was conducted to investigate the effects of differences in estimated biogenic emissions associated with land cover characterization on predicted ozone concentrations using the Comprehensive Air Quality Model with Extensions (CAMx). Mean differences in maximum daily average 8-hour (MDA8) ozone concentrations were 2 to 6 ppb with maximum differences exceeding 20 ppb. Continued focus should be on reducing uncertainties in the representation of land cover through field validation.

Implications: Uncertainties in the estimation of biogenic emissions associated with the characterization of land cover in global and regional data products were examined in eastern Texas. Misclassification between trees and low-growing vegetation in central Texas resulted in substantial differences in isoprene and monoterpene emission estimates and predicted ground-level ozone concentrations. Results from this study indicate the importance of land cover validation at regional scales.     

A comprehensive experimental databank for the models verification of urban car emission dispersion

A summary presentation is made of representative samples from a comprehensive experimental databank on car exhaust dispersion in urban street canyons. Physical modelling, under neutral stratification conditions, was used to provide visualisation, pollutant concentration and velocity measurements above and inside test canyons amidst surrounding urban roughness. The study extended to two different canyon aspects ratios, in combination with different roof configurations on the surrounding buildings. To serve as a reliable basis for validation and testing of urban pollution dispersion codes, special emphasis was placed in this work on data quality assurance.     

Primary sources of selected POPs: regional and global scale emission inventories

During the last decade, a number of studies have been devoted to the sources and emissions of Persistent Organic Pollutants (POPs) at regional and global scales. While significant improvements in knowledge have been achieved for some pesticides, the quantitative understanding of the emission processes and emission patterns for "non-pesticide" POPs are still considered limited. The key issues remaining for the non-pesticide POPs are in part determined by their general source classification. For industrial chemicals, such as the polychlorinated biphenyls (PCBs), there is considerable uncertainty with respect to the relative importance of atmospheric emissions from various source categories. For PCBs, temperature is discussed as a potential key factor influencing atmospheric emission levels and patterns. When it comes to the unintentional by-products of combustion and industrial processes (PCDD/Fs), there is still a large uncertainty with respect to the relative contribution of emissions from unregulated sources such as backyard barrel burning that requires further consideration and characterisation. For hexachlorobenzene (HCB), the relative importance of primary and secondary atmospheric emissions in controlling current atmospheric concentrations remains one of the key uncertainties. While these and other issues may remain unresolved, knowledge concerning the emissions of POPs is a prerequisite for any attempt to understand and predict the distribution and fate of these chemicals on a regional and global scale as well as to efficiently minimise future environmental burdens.     

Inter-provincial responsibility allocation of carbon emission in China to coordinate regional development

Environmental Science and Pollution Research - To establish the carbon emission trading scheme and achieve the carbon emission reduction goals in China, it is critical to allocate the carbon...     

Local to regional emission sources affecting mercury fluxes to New York lakes

Lake-sediment records across the Northern Hemisphere show increases in atmospheric deposition of anthropogenic mercury (Hg) over the last 150 years. Most of the previous studies have examined remote lakes affected by the global atmospheric Hg reservoir. In this study, we present Hg flux records from lakes in an urban/suburban setting of central New York affected also by local and regional emissions. Sediment cores were collected from the Otisco and Skaneateles lakes from the Finger Lakes region, Cross Lake, a hypereutrophic lake on the Seneca River, and Glacial Lake, a small seepage lake with a watershed that corresponds with the lake area. Sediment accumulation rates and dates were established by ²¹⁰Pb. The pre-anthropogenic regional atmospheric Hg flux was estimated to be 3.0 μg m⁻² yr⁻¹ from Glacial Lake, which receives exclusively direct atmospheric deposition. Mercury fluxes peaked during 1971–2001, and were 3 to more than 30 times greater than pre-industrial deposition. Land use change and urbanization in the Otisco and Cross watersheds during the last century likely enhanced sediment loads and Hg fluxes to the lakes. Skaneateles and Glacial lakes have low sediment accumulation rates, and thus are excellent indicators for atmospheric Hg deposition. In these lakes, we found strong correlations with emission records for the Great Lakes region that markedly increased in the early 1900s, and peaked during WWII and in the early 1970s. Declines in modern Hg fluxes are generally evident in the core records. However, the decrease in sediment Hg flux at Glacial Lake was interrupted and has increased since the early 1990s probably due to the operation of new local emission sources. Assuming the global Hg reservoir tripled since the pre-industrial period, the contribution of local and regional emission sources to central New York lakes was estimated to about 80% of the total atmospheric Hg deposition.     

Review of indoor emission source models. Part 1. Overview

Indoor emission source models are mainly used as a component in indoor air quality (IAQ) modeling, which, in turn, is part of exposure and risk modeling. They are also widely used to interpret the experimental data obtained from environmental chambers and buildings. This paper compiles 52 indoor emission source models found in the literature. Together, they represent the achievements that IAQ modelers have made in recent years. While most models have a certain degree of usefulness, genuine predictive models are still few, and there is undoubtedly much room for improvement. This review consists of two parts. Part 1--this paper-provides an overview of the 52 models, briefly discussing their validity, usefulness, limitations, and flaws (if any). Part 2 focuses on parameter estimation, a topic that is critically important to modelers but has not been systematically discussed.     

Comparison of models used for national agricultural ammonia emission inventories in Europe: Litter-based manure systems

Six N-flow models, used to calculate national ammonia (NH₃) emissions from agriculture in different European countries, were compared using standard data sets. Scenarios for litter-based systems were run separately for beef cattle and for broilers, with three different levels of model standardisation: (a) standardized inputs to all models (FF scenario); (b) standard N excretion, but national values for emission factors (EFs) (FN scenario); (c) national values for N excretion and EFs (NN scenario). Results of the FF scenario for beef cattle produced very similar estimates of total losses of total ammoniacal-N (TAN) (±6% of the mean total), but large differences in NH₃ emissions (±24% of the mean). These differences arose from the different approaches to TAN immobilization in litter, other N losses and mineralization in the models. As a result of those differences estimates of TAN available at spreading differed by a factor of almost 3. Results of the FF scenario for broilers produced a range of estimates of total changes in TAN (±9% of the mean total), and larger differences in the estimate of NH₃ emissions (±17% of the mean). The different approaches among the models to TAN immobilization, other N losses and mineralization, produced estimates of TAN available at spreading which differed by a factor of almost 1.7. The differences in estimates of NH₃ emissions decreased as estimates of immobilization and other N losses increased. Since immobilization and denitrification depend also on the C:N ratio in manure, there would be advantages to include C flows in mass-flow models. This would also provide an integrated model for the estimation of emissions of methane, non-methane VOCs and carbon dioxide. Estimation of these would also enable an estimate of mass loss, calculation of the N and TAN concentrations in litter-based manures and further validation of model outputs.     

Review of indoor emission source models. Part 2. Parameter estimation

This review consists of two parts. Part 1 provides an overview of 52 indoor emission source models. Part 2--this paper-focuses on parameter estimation, a topic that is critical to modelers but has never been systematically discussed. A perfectly valid model may not be a useful one if some of its parameters are difficult to estimate in the absence of experimental data. This is true for both statistical and mass transfer models. Forty-eight methods are compiled and reviewed in this paper. Overall, developing methods for parameter estimation has fallen behind the development of models. Such imbalance is the main reason that many models have been left on the shelf since they were published.     

Assessment of the nested grid model estimates for driving regional visibility models in the southwestern United States

The Nested Grid Model (NGM) is a primitive-equation meteorological model that is routinely exercised over North America for forecasting purposes by the National Meteorological Center. While prognostic meteorological models are being increasingly used to drive air quality models, their use in conducting annual simulations requires significant resources. NGM estimates of wind fields and other meteorological variables provide an attractive alternative since they are typically archived and readily available for an entire year. Preliminary evaluation of NGM winds during the summer of 1992 for application to the region surrounding the Grand Canyon National Park showed serious shortcomings. The NGM winds along the borders between California, Arizona and Mexico tend to be northwesterly with a speed of about 6 m/sec, while the observed flow is predominantly southerly at about 2-5 m/sec. The mesoscale effect of a thermal low pressure area over the highly heated Southern California and western Arizona deserts does not appear to be represented by the NGM because of its coarse resolution and the use of sparse observations in that region. Tracer simulations and statistical evaluation against special high resolution observations of winds in the southwest United States clearly demonstrate the northwest bias in NGM winds and its adverse effect on predictions of an air quality model. The "enhanced" NGM winds, in which selected wind observations are incorporated in the NGM winds using a diagnostic meteorological model provide additional confirmation on the primary cause of the northwest bias. This study has demonstrated that in situations where limited resources prevent the use of prognostic meteorological models, previously archived coarse resolution wind fields in which additional observations are incorporated to correct known biases provide an attractive option.     

公交车燃用B5生物柴油的非常规污染物排放特性及对区域大气污染物减排的作用

为推行区域大气污染联合防治并推广使用B5生物柴油,基于重型底盘测功机,采用C-WTVC循环,对比研究满足国Ⅳ、国Ⅴ排放标准的柴油公交车分别燃用国Ⅴ柴油、京Ⅵ柴油和B5生物柴油时的非常规污染物排放特性。结果表明：相比京Ⅵ柴油在采用B5生物柴油后,在不同耐久里程下的所有样车整体上的1,3-C4H6排放因子平均降低20.53%;C6H6排放因子平均降低7.67%;C7H8排放因子平均降低11.22%;HCHO排放因子平均降低14.92%;SO2排放因子平均降低6.09%。实验证明城市公交车在燃用B5生物柴油后的非常规污染物排放均降低。城市公交车推广使用B5生物柴油可有效净化大气质量,对区域大气污染物减排有着重要意义。     

Comparison of solubility databases used for HLW performance assessment

Elemental solubility limits are employed in many performance assessment studies of the disposal of high-level radioactive waste. A comparison of solubility databases used in a number of recent assessments from Canada, Finland, Japan, Sweden, Switzerland and the U.S.A. is presented. Despite similarities in the chemical conditions under which such solubilities are defined, there are very large ranges in the values selected for most elements (several orders of magnitude). In some cases, differences in solubilities can be attributed to differences in the thermodynamic databases used but, due to generally incomplete documentation, both of such databases and the criteria for data selection, detailed analysis of the reason for such discrepancies is precluded. A key factor, however, is the fairly subjective choice of the solid phase considered to be “solubility-limiting”. Procedures are recommended which would increase the transparency of solubility database compilation in future analyses.     

Evaluation of low wind modeling approaches for two tall-stack databases

The performance of the AERMOD air dispersion model under low wind speed conditions, especially for applications with only one level of meteorological data and no direct turbulence measurements or vertical temperature gradient observations, is the focus of this study. The analysis documented in this paper addresses evaluations for low wind conditions involving tall stack releases for which multiple years of concurrent emissions, meteorological data, and monitoring data are available. AERMOD was tested on two field-study databases involving several SO₂ monitors and hourly emissions data that had sub-hourly meteorological data (e.g., 10-min averages) available using several technical options: default mode, with various low wind speed beta options, and using the available sub-hourly meteorological data. These field study databases included (1) Mercer County, a North Dakota database featuring five SO₂ monitors within 10 km of the Dakota Gasification Company’s plant and the Antelope Valley Station power plant in an area of both flat and elevated terrain, and (2) a flat-terrain setting database with four SO₂ monitors within 6 km of the Gibson Generating Station in southwest Indiana. Both sites featured regionally representative 10-m meteorological databases, with no significant terrain obstacles between the meteorological site and the emission sources. The low wind beta options show improvement in model performance helping to reduce some of the overprediction biases currently present in AERMOD when run with regulatory default options. The overall findings with the low wind speed testing on these tall stack field-study databases indicate that AERMOD low wind speed options have a minor effect for flat terrain locations, but can have a significant effect for elevated terrain locations. The performance of AERMOD using low wind speed options leads to improved consistency of meteorological conditions associated with the highest observed and predicted concentration events. The available sub-hourly modeling results using the Sub-Hourly AERMOD Run Procedure (SHARP) are relatively unbiased and show that this alternative approach should be seriously considered to address situations dominated by low-wind meander conditions.

Implications: AERMOD was evaluated with two tall stack databases (in North Dakota and Indiana) in areas of both flat and elevated terrain. AERMOD cases included the regulatory default mode, low wind speed beta options, and use of the Sub-Hourly AERMOD Run Procedure (SHARP). The low wind beta options show improvement in model performance (especially in higher terrain areas), helping to reduce some of the overprediction biases currently present in regulatory default AERMOD. The SHARP results are relatively unbiased and show that this approach should be seriously considered to address situations dominated by low-wind meander conditions.     

Effects of sulfur dioxide and oxides of nitrogen emission reductions on fine particulate matter mass concentrations: regional comparisons

Two thermodynamic equilibrium models were applied to estimate changes in mean airborne fine particle (PM2.5) mass concentrations that could result from changes in ambient concentrations of sulfate, nitric acid, or ammonia in the southeastern United States, the midwestern United States, and central California. Pronounced regional differences were found. Southeastern sites exhibited the lowest current mean concentrations of nitrate, and the smallest predicted responses of PM2.5 nitrate and mass concentrations to reductions of nitric acid, which is the principal reaction product of the oxidation of nitrogen dioxide (NO2) and the primary gas-phase precursor of fine particulate nitrate. Weak responses of PM2.5 nitrate and mass concentrations to changes in nitric acid levels occurred even if sulfate concentrations were half of current levels. The midwestern sites showed higher levels of fine particulate nitrate, characterized by cold-season maxima, and were projected to show decreases in overall PM levels following decreases of either sulfate or nitric acid. For some midwestern sites, predicted PM2.5 nitrate concentrations increased as modeled sulfate levels declined, but sulfate reductions always reduced the predicted fine PM mass concentrations; PM2.5 nitrate concentrations became more sensitive to reductions of nitric acid as modeled sulfate concentrations were decreased. The California sites currently have the highest mean concentrations of fine PM nitrate and the lowest mean concentrations of fine PM sulfate. Both the estimated PM2.5 nitrate and fine mass concentrations decreased in response to modeled reductions of nitric acid at all California sites. The results indicate important regional differences in expected PM2.5 mass concentration responses to changes in sulfate and nitrate precursors. Analyses of ambient data, such as described here, can be a key part of weight of evidence (WOE) demonstrations for PM2.5 attainment plans. Acquisition of the data may require special sampling efforts, especially for PM2.5 precursor concentration data.     

水泥厂氨排放标准存在的问题及氨排放控制

为控制水泥脱硝工程产生的氨排放问题,中国发布《水泥工业大气污染物排放标准》(GB 4915—2013)对水泥企业氨排放限值提出明确要求。但水泥脱硝设施同步配套的氨在线检测仪记录数据表明,多数水泥厂脱硝后的氨排放浓度远超过标准限值。为此,对照火电厂相关标准和技术规范,指出了水泥工业氨排放标准和技术规范文件中存在的问题。结合实际检测数据和国外相关文献,确认水泥工业存在"本底氨"排放,水泥原料、协同处理废弃物、生产工况变化是导致本底氨排放的主要原因。选择性非催化还原(SNCR)脱硝设施产生的氨逃逸将增加氨排放浓度,反应温度窗口、停留时间、氨/氮摩尔比(NSR)、喷射方案等均会影响氨逃逸浓度。优化水泥生产工艺、SNCR脱硝工艺或配套选择性催化还原(SCR)脱硝系统等方式可有效控制水泥厂本底氨及氨逃逸。