环境空气质量评价的普适指数公式

在适当设定空气污染物的基准值和用相对于基准值的空气污染物的“相对”值情况下,采用S型曲线表示空气污染物对环境空气质量的危害程度,并应用遗传算法优化公式中的参数,得出了一个对多种空气污染物通用的环境空气质量评价的普适指数公式。借助于折衷型激励功效函数将单基污染物分指数加权为综合指数。该公式形式简单,容量计算、评价结果精度较高,且具有可比性。     

兼顾异味污染物的环境空气质量综合评价案例研究

异味污染是人们比较敏感的一种大气环境污染,是影响公众对空气质量满意程度的一个重要方面,也是导致公众的直接感官与官方发布的空气质量指数(AQI)存在落差的原因之一。以江苏省某大学城地区为对象,建立了一种兼顾常规污染物和异味污染物的环境空气质量综合评价方法,并引入异味指数分级方案,将公众的异味投诉强度纳入到综合评价指标体系中。结果表明,2013年该地区的综合评价结果相比只基于常规污染物的评价结果,空气质量下降明显。此评价方法为异味污染评价提供了一次尝试,有利于完善现有的空气质量评价体系,具有一定的应用价值。     

基于Г型分布的空气质量评价普适指数公式

在设定各项空气污染物的浓度“参照值”基础上,提出了一个适用于多项空气污染物的Г型分布空气质量评价普适指数公式。采用基于实数编码的遗传算法对公式中的参数优化,得出优化后适用于多项空气污染物的空气质量评价普适指数公式。公式被应用于多个实例分析计算,并与其他若干评价方法评价结果相比较,结果表明,该公式不受空气污染物种类和数目多少的限制。公式形式简单,计算快速,具有可比性、通用性和实用性。     

基于主成分和粒子群优化支持向量机的水质评价模型

水质的评价是治理水污染必不可少的工作。为了准确、快速地对水质进行评价,利用主成分分析法从水质监测常见的多个物化指标提取出主成分,然后将主成分作为支持向量分类机的输入,利用历史数据进行水质评价训练并用粒子群算法优化参数,构造出水质评价模型,将从物化指标中得出的主成分代入此模型即可得到水质类别。最后,选取水质监测点实测数据进行试验,结果表明,模型的水质评价结果准确且稳定。     

混沌粒子群算法在水污染控制系统规划中的应用

针对常用的最优化方法解决水污染控制系统规划问题运算过程较复杂,容易陷入局部极值,且优化解精度不高的情况,尝试利用混沌方法和粒子群算法相结合的混沌粒子群算法(chaos particle swarm optimization,CPSO)求解此类问题。CPSO算法具有原理简单,且能快速获得最优解的特点。在实例应用中与遗传算法和MATLAB优化函数的优化结果做了比较,CPSO算法的性能以及得到的解明显优于后两种方法,验证了该方法的可行性和有效性。     

基于变异CPSO算法的LSSVM出水COD的软测量研究

在分析混沌粒子群优化算法(CPSO)和最小二乘支持向量机(SVM)理论基础上,以某污水处理厂的氧化沟系统为对象,采用带有末位淘汰机制的混沌粒子群优化算法优化支持向量机的参数,建立了基于变异CPSO算法的LS-SVM的氧化沟出水水质COD软测量模型,并与PSO-LSSVM,LSSVM模型比较,研究表明,ICPSO-LSSVM模型预测准确,泛化性能好,且该模型预测结果中相对误差小于10%的样本达到90%,最大相对误差仅为12.5%,均方差MSE为0.0106,模型具有较高的精度,基本可以实现出水COD浓度的在线预估。     

江苏省污染减排与空气质量变化相关性分析

利用2000—2007年大气污染物排放量数据和同期环境空气质量监测数据,分析了江苏省主要大气污染物减排与环境空气质量变化的相关性。结果表明,近年来江苏省SO2排放量与环境空气中SO2浓度存在正相关,而烟尘和粉尘排放总量与空气中可吸入颗粒物的浓度呈现出弱的负相关关系。对江苏省经济发展和环境关系的进一步分析揭示,江苏省环境库兹涅茨曲线呈现出倒U型关系,表明江苏省已经进入经济环境双赢区间,但近年来政策对经济环境关系的影响突出。该研究对中国十二五环境管理政策的制定有着重要的参考意义。     

杭州城市可吸入颗粒物污染与气象条件关系的分级评价和BP神经网络评估

为了解杭州城市环境空气质量与气象条件之间的关系,利用杭州市区2003-2007年的可吸入颗粒物(PM10)浓度数据和气象资料,通过分级评价的方法和基于BP神经网络的污染物浓度评估模型,得到PM10浓度与气象条件的对应关系.结果表明,随着日降水量的增大,PM10浓度减小;风速与PM10浓度呈明显的负相关,随着风速的增大,PM10浓度明显减小;气象因素与PM10浓度之间呈非线性关系,大气能见度对PM10和相对湿度的变化极为敏感.随着PM10浓度的增大,大气能见度迅速降低,相对湿度越高,大气能见度则越低;近几年杭州市气象条件不利于大气污染物的扩散和清洗,是杭州城市环境空气质量上升缓慢的主要原因之一.     

环境保护部印发落实大气十条严格环评准入通知防治重点区域实施环评会商

正为贯彻落实《大气污染防治行动计划》,从源头预防环境污染,促进环境空气质量改善,环境保护部近日印发了《关于落实大气污染防治行动计划严格环境影响评价准入的通知》(以下简称《通知》)。《通知》要求,要进一步发挥规划环境影响评价的调控、引领和约束作用,强调规划环境影响评价在促进产业结构调整和优化城市总体规划中的作用和地位。要以促进大气污染物减排、改善环境空气质     

等效排气筒有效高度计算方法的比选及其应用于大气污染预测的可行性

目前,等效排气筒多用于大气污染物总量控制,其预测精度和范围的不明晰限制了其在污染物运移扩散领域的进一步应用。基于《大气污染物综合排放标准》,依据所预测的范围和浓度精度对8种典型等效计算方法进行了比选,并验证了将等效排气筒用于不同工况下污染物运移扩散预测的可行性。改进的有效高度等效算法(源强加权算术平均法)综合考虑了不同高度和源强参数特征,以2个排放同种污染物的相邻排气筒为例,所计算的高斯模式下等效后下风向污染物浓度场总体分布趋势与等效前叠加计算结果一致,且预测精度优于《大气污染物综合排放标准》中提出的均方根平均法和其他等效算法。对不同风速条件下(1.5～4.5 m·s-1)等效前后下风向污染物浓度场分布计算比较,发现即使风速改变仍可保证较高的最大落地浓度预测精度(-6.87%～-2.21%),特别是风速较大时其预测精度更高(达到-2.21%)。这验证了该方法的有效性和稳定性。本研究探讨的源强加权算术平均值算法,进一步提升了等效排气筒相关参数计算的合理性,并拓展了其在大气预测评价中的应用。     

A real-time monitoring and assessment method for calculation of total amounts of indoor air pollutants emitted in subway stations

Subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, in this study, a new cumulative calculation method for the estimation of total amounts of indoor air pollutants emitted inside the subway station is proposed by taking cumulative amounts of indoor air pollutants based on integration concept. Minimum concentration of individual air pollutants which naturally exist in indoor space is referred as base concentration of air pollutants and can be found from the data collected. After subtracting the value of base concentration from data point of each data set of indoor air pollutant, the primary quantity of emitted air pollutant is calculated. After integration is carried out with these values, adding the base concentration to the integration quantity gives the total amount of indoor air pollutant emitted. Moreover the values of new index for cumulative indoor air quality obtained for 1 day are calculated using the values of cumulative air quality index (CAI). Cumulative comprehensive indoor air quality index (CCIAI) is also proposed to compare the values of cumulative concentrations of indoor air pollutants. From the results, it is clear that the cumulative assessment approach of indoor air quality (IAQ) is useful for monitoring the values of total amounts of indoor air pollutants emitted, in case of exposure to indoor air pollutants for a long time. Also, the values of CCIAI are influenced more by the values of concentration of NO2, which is released due to the use of air conditioners and combustion of the fuel. The results obtained in this study confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well. Implications: Nowadays, subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in the indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, this paper presents a new methodology for monitoring and assessing total amounts of indoor air pollutants emitted inside underground spaces and subway stations. A new methodology for the calculation of cumulative amounts of indoor air pollutants based on integration concept is proposed. The results suggest that the cumulative assessment approach of IAQ is useful for monitoring the values of total amounts of indoor air pollutants, if indoor air pollutants accumulated for a long time, especially NO2 pollutants. The results obtained here confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well.     

基于智能优化算法的河流水质模型参数的优化

为探索河流水质模型参数新的求解方法,根据有限的实测数据,分别应用免疫进化优化算法和免疫进化优选的捕食搜索算法,对河流水质模型计算公式中的多参数进行优化。将优化得到的计算公式用于国内外若干河流的河段中DO浓度值的拟合,并与实测结果进行了比较。结果表明,将免疫进化优化算法或免疫进化优选的捕食搜索算法优化得到的水质模型参数精度不仅较高,而且相对稳定,从而为河流水质模型参数的优化提供了一种新方法。     

基于智能优化算法的河流水质模型参数的优化简

为探索河流水质模型参数新的求解方法,根据有限的实测数据,分别应用免疫进化优化算法和免疫进化优选的捕食搜索算法,对河流水质模型计算公式中的多参数进行优化。将优化得到的计算公式用于国内外若干河流的河段中DO浓度值的拟合,并与实测结果进行了比较。结果表明,将免疫进化优化算法或免疫进化优选的捕食搜索算法优化得到的水质模型参数精度不仅较高,而且相对稳定,从而为河流水质模型参数的优化提供了一种新方法。     

Derivation of exemption formulas for air quality regulatory applications

The regulatory agencies and the industries have the responsibility for assessing the environmental impact from the release of air pollutants, and for protecting environment and public health. The simple exemption formula is often used as a criterion for the purpose of screening air pollutants. That is, the exemption formula is used for air quality review and to determine whether a facility applying for and described in a new, modified, or revised air quality plan is exempted from further air quality review. The Bureau of Ocean Energy Management’s (BOEM) air quality regulations are used to regulate air emissions and air pollutants released from the oil and gas facilities in the Gulf of Mexico. If a facility is not exempt after completing the air quality review, a refined air quality modeling will be required to regulate the air pollutants. However, at present, the scientific basis for BOEM’s exemption formula is not available to the author. Therefore, the purpose of this paper is to provide the theoretical framework and justification for the use of BOEM’s exemption formula. In this paper, several exemption formulas have been derived from the Gaussian and non-Gaussian dispersion models; the Gaussian dispersion model is a special case of non-Gaussian dispersion model. The dispersion parameters obtained from the tracer experiments in the Gulf of Mexico are used in the dispersion models. In this paper, the dispersion parameters used in the dispersion models are also derived from the Monin-Obukhov similarity theory. In particular, it has been shown that the total amount of emissions from the facility for each air pollutant calculated using BOEM’s exemption formula is conservative.

Implications:?The operation of offshore oil and gas facilities under BOEM’s jurisdiction is required to comply with the BOEM’s regulations. BOEM’s air quality regulations are used to regulate air emissions and air pollutants released from the oil and gas facilities in the Gulf of Mexico. The exemption formulas have been used by BOEM and other regulatory agencies as a screening tool to regulate air emissions emitted from the oil and gas and other industries. Because of the BOEM’s regulatory responsibility, it is important to establish the scientific basis and provide the justification for the exemption formulas. The methodology developed here could also be adopted and used by other regulatory agencies.     

A real-time monitoring and assessment method for calculation of total amounts of indoor air pollutants emitted in subway stations

Subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, in this study, a new cumulative calculation method for the estimation of total amounts of indoor air pollutants emitted inside the subway station is proposed by taking cumulative amounts of indoor air pollutants based on integration concept. Minimum concentration of individual air pollutants which naturally exist in indoor space is referred as base concentration of air pollutants and can be found from the data collected. After subtracting the value of base concentration from data point of each data set of indoor air pollutant, the primary quantity of emitted air pollutant is calculated. After integration is carried out with these values, adding the base concentration to the integration quantity gives the total amount of indoor air pollutant emitted. Moreover, the values of new index for cumulative indoor air quality obtained for 1 day are calculated using the values of cumulative air quality index (CAI). Cumulative comprehensive indoor air quality index (CCIAI) is also proposed to compare the values of cumulative concentrations of indoor air pollutants. From the results, it is clear that the cumulative assessment approach of indoor air quality (IAQ) is useful for monitoring the values of total amounts of indoor air pollutants emitted, in case of exposure to indoor air pollutants for a long time. Also, the values of CCIAI are influenced more by the values of concentration of NO₂, which is released due to the use of air conditioners and combustion of the fuel. The results obtained in this study confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well.

Implications: Nowadays, subway systems are considered as main public transportation facility in developed countries. Time spent by people in indoors, such as underground spaces, subway stations, and indoor buildings, has gradually increased in the recent past. Especially, operators or old persons who stay in the indoor environments more than 15 hr per day usually influenced a greater extent by indoor air pollutants. Hence, regulations on indoor air pollutants are needed to ensure good health of people. Therefore, this paper presents a new methodology for monitoring and assessing total amounts of indoor air pollutants emitted inside underground spaces and subway stations. A new methodology for the calculation of cumulative amounts of indoor air pollutants based on integration concept is proposed. The results suggest that the cumulative assessment approach of IAQ is useful for monitoring the values of total amounts of indoor air pollutants, if indoor air pollutants accumulated for a long time, especially NO₂ pollutants. The results obtained here confirm that the proposed method can be applied to monitor total amounts of indoor air pollutants emitted, inside apartments and hospitals as well.     

Monte Carlo simulation of buoyant dispersion

Transport and diffusion of dust and nonbuoyant smoke are simulated in a realistic manner by the particle model originally developed by Ohmstede and Stenmark (1980, 1981). However, many pollutants are buoyant, such as burning trash, oil, or other flammable or explosive material. The resultant buoyant cloud is taken into account by a new simple algorithm included in the particle model. For the model discussed in this paper, a particle represents a small parcel of air plus pollutant. The method uses the difference in temperature between an individual particle and the ambient atmosphere to generate a vertical acceleration. It also considers entrainment and ingestion of unheated material on, or loss of heat by contact with, the ground during initial release and subsequent ground contact. A series of computer runs suggests that the particle model with the new buoyancy algorithm realistically simulates transport and diffusion of buoyant material.     

Modeling and optimization of wet flue gas desulfurization system based on a hybrid modeling method

Sulfur dioxide (SO₂) is one of the main air pollutants from many industries. Most coal-fired power plants in China use wet flue gas desulfurization (WFGD) as the main method for SO₂ removal. Presently, the operating of WFGD lacks accurate modeling method to predict outlet concentration, let alone optimization method. As a result, operating parameters and running status of WFGD are adjusted based on the experience of the experts, which brings about the possibility of material waste and excessive emissions. In this paper, a novel WFGD model combining a mathematical model and an artificial neural network (ANN) was developed to forecast SO₂ emissions. Operation data from a 1000-MW coal-fired unit was collected and divided into two separated sets for model training and validation. The hybrid model consisting a mechanism model and a 9-input ANN had the best performance on both training and validation sets in terms of RMSE (root mean square error) and MRE (mean relative error) and was chosen as the model used in optimization. A comprehensive cost model of WFGD was also constructed to estimate real-time operation cost. Based on the hybrid WFGD model and cost model, a particle swarm optimization (PSO)-based solver was designed to derive the cost-effective set points under different operation conditions. The optimization results demonstrated that the optimized operating parameters could effectively keep the SO₂ emissions within the standard, whereas the SO₂ emissions was decreased by 30.79% with less than 2% increase of total operating cost.

Implications: Sulfur dioxide (SO₂) is one of the main pollutants generated during coal combustion in power plants, and wet flue gas desulfurization (WFGD) is the main facility for SO₂ removal. A hybrid model combining SO₂ removal mathematical model with data-driven model achieves more accurate prediction of outlet concentration. Particle swarm optimization with a penalty function efficiently solves the optimization problem of WFGD subject to operation cost under multiple operation conditions. The proposed model and optimization method is able to direct the optimized operation of WFGD with enhanced emission and economic performance.     

建筑物对高架点源大气污染物扩散影响的模拟研究

运用数值方法对城市中高架点源排放大气污染物的扩散规律进行了模拟研究,在计算区域内建立了三维数学模型,并将拉格朗日法描述的颗粒轨道模型耦合到风场。本研究计算了地面风速为3 m/s时的大气流场,并模拟研究了该风场条件下气体污染物的扩散和固体颗粒污染物的运动轨迹。通过分析模拟结果,给出了高架点源中排放的气体污染物的扩散区域和固体颗粒污染物运动轨迹的变化规律。