支撑京津冀区域大气污染联防联控的大气监测体系构建

京津冀区域已成为全国大气污染最严重的地区之一,并且呈现出明显的区域性污染特征,加强区域间的环境合作,实施区域联防联控是解决京津冀区域大气污染问题的有效手段。对照《生态环境监测网络建设方案》的要求,目前京津冀区域大气监测体系还存在着监测网络不健全、监测项目覆盖不全面、监测新技术应用不足、质控体系不完善、信息产品供给与公众需求有差距等问题,与京津冀区域大气污染联防联控的要求不相适应。为全面提升京津冀区域大气监测体系对区域联防联控的技术支撑能力,亟需进一步完善京津冀区域的监测网络,增设传输研究、污染监控等特殊监测点位;逐步拓展监测项目,开展颗粒物化学组分和O_3前体物监测;加快遥感监测等立体监测技术在大气监测中的应用,全面分析污染物时空分布特征与传输规律;加强空气质量预报预警能力建设,为重污染天气应对提供技术支持;规范监测事权上收后的全过程质控体系,建立颗粒物标准方法比对和O_3量值传递质控机制;构建环境监测大数据平台,加强数据分析应用与信息公开。     

上海市工业区大气污染预警监测信息平台研究与设计

根据上海市工业区大气污染排放特征,在构建大气特征污染监控网络的基础上,搭建了工业区大气污染预警监测信息平台,并研究了适用于大气特征污染自动站的通信传输规范,确保数据联网和应用。平台设置了大气质量监控、大气数据管理、污染源一厂一档、大气质量分析评价、污染源溯源分析、应急监测数据管理、智能移动终端查询等7个子系统,可为上海市工业区大气污染预警和管控提供实时监测数据。     

大连市臭氧污染特征及典型污染日成因

通过对大连市区10个空气监测子站的监测数据进行分析,探讨了大连市臭氧污染的时空分布、气象条件对臭氧污染的影响,对臭氧污染日进行了归类分析。结果表明,大连市臭氧污染主要出现在4—10月。在强紫外辐射、高温、低湿、低压和低风速的气象条件下,监测点位的臭氧浓度较高。臭氧污染日的日变化分为单峰型、双峰型和夜间持续升高型3种类型。通过对2015年的一次高浓度臭氧污染过程的气象条件、污染物浓度和污染气团轨迹进行分析,发现臭氧浓度在夜间持续升高现象与区域输送密切相关。     

2015年新疆阿克苏市沙尘污染与气象因素关系的分析

应用阿克苏市国家基准站及2个环保局监测站2015年大风沙尘天气过程前后PM10浓度变化及其与污染源、NECP全球再分析资料、风、监测站周边环境等关系进行分析.结果表明,阿克苏市春季沙尘天气的首要污染物均为PM10,PM10的变化曲线呈正态分布,春季中度及以上污染日均出现在污染日当日或次日.造成阿克苏市沙尘天气污染源分本地型、外来型以及二者共同影响型三种.本地型沙尘污染强度取决于北风风速大小及强风持续时间,PM10浓度变化与风速呈正相关.而外来型污染多发生在本地型沙尘天气之后,"东灌"冷空气裹挟沙尘进入南疆盆地,造成地面加压,浮尘天气造成PM10浓度增大,并持续数天.总结出沙尘天气污染预警的几个必要条件,后续在地区环保局、县局监测站建立的情况下,为分析阿克苏地区"八县一市"污染物与气象因素的关系提供借鉴,同时为实际的空气质量预警提供参考.     

Investigating the impacts of some meteorological parameters on air pollution in Balikesir, Turkey

Air pollution is one of the most important environmental problems in Balikesir, situated in the western part of Turkey, during the winter periods. The unfavorable climate as well as the city’s topography, and inappropriate fuel usage cause serious air pollution problems. The air pollutant concentrations in the city have a close relationship with meteorological parameters. In the present study, the relationship between daily average total suspended particulate (TSP) and sulphur dioxide (SO₂) concentrations measured between 1999–2005 winter seasons were correlated with meteorological factors, such as wind speed, temperature, relative humidity and pressure. This statistical analysis was achieved using the stepwise multiple linear regression method. According to the results obtained through the analysis, higher TSP and SO₂ concentrations are strongly related to colder temperatures, lower wind speed, higher atmospheric pressure and higher relative humidity. The statistical models of SO₂ and TSP gave correlation coefficient values (R ²) of 0.735 and 0.656, respectively.     

上海市路边环境空气黑碳气溶胶污染特征及影响因素研究

为研究上海市路边环境空气黑碳(BC)的污染特征,采用连续监测方法对2016年1月至2018年12月上海市路边环境空气BC浓度进行了监测,并同步监测了气象因子,分析了BC的时间变化特征,探讨了气象因素对BC的影响以及不同空气质量等级下BC浓度水平。结果表明:2016、2017、2018年上海市路边环境空气BC年均质量浓度分别为(2 908±2 189)、(2 959±2 224)、(2 824±2 002) ng/m3,呈现出下降趋势;2016、2017、2018年BC与PM2.5年均质量浓度比分别为9. 30%、9. 20%、9. 50%;BC季节变化特征明显,整体表现为春夏高、秋冬低的特点;昼夜变化特征均呈现出双峰分布,第一个峰值均出现在06:00,第二个峰值均出现在16:00-19:00,且第一个峰值高于第二个峰值。气象因素对BC有一定影响,在降水、相对湿度低以及非静风条件下BC浓度较低。随着上海市空气质量由好转差,上海市路边环境空气BC浓度均呈现上升趋势,空气质量为良、轻度污染、中度污染、重度污染时路边环境空气BC平均浓度分别较空气质量为优时增加了0. 38、0. 96、1. 61、1. 96倍。     

基于卫星数据的灰霾污染遥感监测方法及系统设计

以中分辨率成像光谱仪为例,建立了卫星遥感参数和空气污染指标之间的联系,提出了基于卫星遥感的气溶胶光学厚度数据获得灰霾指数和灰霾污染时空气质量指数(AQI)等级的方法和相关的监测系统设计。结合在华北地区的监测结果,可以看出卫星遥感可以较好地反映灰霾污染程度的变化,有助于发现可能的传输通道,获得宏观的灰霾空间分布状况。在研究时段内,与地面空气质量监测站相比,88%的卫星遥感监测结果误差不大于1个AQI等级,平均的AQI等级偏差为0.7级,并分析了卫星遥感与地面监测之间差异的原因。     

Modeling of SO<Subscript>2</Subscript> distribution in Istanbul using artificial neural networks

Urban air pollution is a growing problem in developing countries. Some compounds especially sulphur dioxide (SO₂) is considered as typical indicators of the urban air quality. Air pollution modeling and prediction have great importance in preventing the occurrence of air pollution episodes and provide sufficient time to take the necessary precautions. Recently, various stochastic image-processing algorithms such as Artificial Neural Network (ANN) are applied to environmental engineering. ANN structure employs input, hidden and output layers. Due to the complexity of the problem, as the number of input–output parameters differs, ANN model settings such as the number of neurons of these layers changes. The ability of ANN models to learn, particularly capability of handling large amounts (or sets) of data simultaneously as well as their fast response time, are invariably the characteristics desired for predictive and forecasting purposes. In this paper, ANN models have been used to predict air pollutant parameter in meteorological considerations. We have especially focused on modeling of SO₂ distribution and predicting its future concentration in Istanbul, Turkey. We have obtained data sets including meteorological variables and SO₂ concentrations from Istanbul-Florya meteorological station and Istanbul-Yenibosna air pollution station. We have preferred three-layer perceptron type of ANN which consists of 10, 22 and 1 neurons for input, hidden and output layers, respectively. All considered parameters are measured as daily mean. The input parameters are: SO₂ concentration, pressure, temperature, humidity, wind direction, wind speed, strength of sunshine, sunshine, cloudy, rainfall and output parameter is the future prediction of SO₂. To evaluate the performance of ANN model, our results are compared to classical nonlinear regression methods. The over all system finds an optimum correlation between input–output variables. Here, the correlation parameter, r is 0.999 and 0.528 for training and test data. Thus in our model, the trend of SO₂ is well estimated and seasonal effects are well represented. As a result, we conclude that ANN is one of the compromising methods in estimation of environmental complex air pollution problems.     

北方沙尘对江苏环境空气中可吸入颗粒物浓度的影响

利用卫星遥感数据、气象观测资料和江苏省环境空气自动站的可吸入颗粒物的监测数据,对春季中国北方的沙尘暴过程对江苏环境空气中可吸入颗粒物浓度的影响分析发现,沙尘暴所含的沙尘粒子在冷空气的引导下可能进入江苏,对环境空气中可吸入颗粒物浓度将会产生较大的影响;北方沙尘暴所携带的沙尘粒子是春季江苏空气污染的重要来源之一,是预报空气质量异常偏高的重要依据之一。     

融合拓扑信息与气象信息的空气质量预测网络

通过空气质量监测数据对正在形成或即将到来的空气污染进行预测是一项具有重要意义的工作，而空气质量监测站只能检测其周围一定范围内的空气污染情况。为了衡量整个城市的空气污染情况，获取任意时间、任意位置的空气质量信息，结合交叉注意力机制，提出了一种融合拓扑信息与气象信息的空气质量预测网络(CGMIM)。将西安市空气质量监测数据与气象数据转换为图像拼接起来，作为输入信息。在高阶非线性时空动态神经网络(MIM)的基础上引入注意力机制，并增加拓扑图编码器模块，提高模型提取能力以及对空气质量监测数据中的空间特征的利用率。最后，使用时空损失函数替代传统的均方误差损失函数，提高模型对空间关系的关注。结果表明：CGMIM网络模型能够在准确预测的同时，对位置区域合理填充，能够有效提升空气质量监测数据的空间分辨率。     

北京市2013年1月一次空气重污染过程分析

采用数值模式与观测资料相结合的方式，对北京市2013年1月9～15日一次空气重污染过程的大气环境背景、气象条件和形成原因进行了初步分析。结果表明，此次重污染过程北京市空气质量从9日的二级跳至10日五级重度污染，11日一13日空气质量维持连续3d严重污染，14日降为重度污染，15日转为轻度污染；重污染过程期间10—14日P（PM2.5）平均值为323μg／m。，平均风速为1．47m／s，平均相对湿度为73．6％，24h变温基本为一2．72～2．68℃，24h平均变压为一3．65～2．63hPa。指出，此次重污染过程与当地气象条件密切相关，稳定的大气环流形势为污染的持续提供了大气环流背景，风速较小、湿度较大、边界层较低、持续逆温是造成重污染的主要原因，地面风场辐合及边界层下沉运动是造成重污染的重要原因。     

气体中毒窒息事故的环境应急监测

以株洲市攸县某矿业公司"5·7"重大中毒窒息事故的环境应急监测为例，详细阐述了该事故开展应急监测的全过程。针对锁定污染因子、查找污染源、判断污染团的扩散趋势以及监控敏感点的安全等监测目的设计监测方案。通过监测数据分析确定事故特征因子为CO，其周边环境空气中浓度随着与抽风口距离的增加而快速下降，监测到附近居民区环境空气质量未受事故影响。     

支撑排污许可制度的固定源监测技术体系完善研究

排污许可制度是固定源核心管理制度,对污染源监测技术提出"便捷、智能、精细"的发展要求,依规发证、依证管理2个阶段均需要污染源监测技术的有效支撑。针对当前污染源监测技术体系现状,应进一步完善自行监测技术指南体系,对发证行业指南实施情况跟踪评估,适时修订;为将工业园区纳入核发排污许可证范围扎牢基础,制定工业园区自行监测技术指南;加快构建支撑证后监管执法的快速便捷方法标准体系和现场快速监测质控体系;加快构建智能化监测数据管理平台,实现"智慧大脑"功能;建立自行监测监督检查技术体系,强化排污许可制度框架下的自行监测质量的监督检查。     

Risk-Based Prioritization of Air Pollution Monitoring Using Fuzzy Synthetic Evaluation Technique

Air pollution monitoring programs aim to monitor pollutants and their probable adverse effects at various locations over concerned area. Either sensitivity of receptors/location or concentration of pollutants is used for prioritizing the monitoring locations. The exposure-based approach prioritizes the monitoring locations based on population density and/or location sensitivity. The hazard-based approach prioritizes the monitoring locations using intensity (concentrations) of air pollutants at various locations. Exposure and hazard-based approaches focus on frequency (probability of occurrence) and potential hazard (consequence of damage), respectively. Adverse effects should be measured only if receptors are exposed to these air pollutants. The existing methods of monitoring location prioritization do not consider both factors (hazard and exposure) at a time. Towards this, a risk-based approach has been proposed which combines both factors: exposure frequency (probability of occurrence/exposure) and potential hazard (consequence).This paper discusses the use of fuzzy synthetic evaluation technique in risk computation and prioritization of air pollution monitoring locations. To demonstrate the application, common air pollutants like CO, NO_x, PM₁₀ and SO_x are used as hazard parameters. Fuzzy evaluation matrices for hazard parameters are established for different locations in the area. Similarly, fuzzy evaluation matrices for exposure parameters: population density, location and population sensitivity are also developed. Subsequently, fuzzy risk is determined at these locations using fuzzy compositional rules. Finally, these locations are prioritized based on defuzzified risk (crisp value of risk, defined as risk score) and the five most important monitoring locations are identified (out of 35 potential locations). These locations differ from the existing monitoring locations.     

Multi-objective optimization of air quality monitoring

A new method for multi-objective optimization of air quality monitoring systems based on satellite remote sensing of the troposphere is described in this work. The technique uses atmospheric turbidity as surrogate for air pollution loading. Through inverse chemical modeling and ancillary information the respective patterns of primary gaseous and particle pollutants are inferred. The optimization algorithm uses the resulting maps of ambient air pollution as input. It focuses on the gain of information with regard to human exposure to high pollution, potential impact on cultural heritage, compliance to ambient air quality standards, monitoring key point and area source emissions, as well as on the associated cost. Application of the method in Brescia, Italy showed its significant potential for improving the cost-effectiveness of air quality monitoring networks at the urban and regional scales.     

不同天气形势下杭州市空气污染特征个例分析

利用杭州市气象局观测资料、NCEP再分析资料和中尺度天气预报模式WRF的数值模拟结果,对杭州市2011—2012年春、夏、秋、冬4个季节各一天的污染天气进行分析;同时选取2012年夏季有利于污染物扩散的天气个例进行对比分析。结果表明,杭州市容易发生轻度污染的天气类型主要有4类:高压前部、高压底部、高压控制和高压后部;500 h Pa高空系统稳定,受西南气流影响,850 h Pa有暖平流,1 000 h Pa风速较小时,容易造成污染物的积累,发生空气污染现象。WRF模拟结果显示,当杭州市为偏北风且风速较小时,容易发生空气污染事件,当为偏南风且风速较大时,空气质量一般较好。温度层结分析发现,当近地层以及高空出现较为深厚的逆温层且低层温度层结呈现中性或者稳定时,不利于污染物的扩散,污染物容易在底层积累,出现近地层空气污染现象。     

基于空间计量模型的四川省大气污染特征及影响因素分析

四川省细颗粒物污染问题越来越受到重视,为有效识别四川省大气污染空间分布情况及影响因素,利用2015—2020年PM_2.5监测数据,综合分析了四川省大气污染时空分布特征,选取同期气象要素观测数据和社会经济数据,区分出全省及省内不同经济区大气污染的主要影响因素。结果表明:2015—2020年四川省的PM_2.5浓度逐年下降,日变化存在明显的双峰双谷趋势,且具有明显季节性特征,空间分布上具有明显的空间聚集现象;PM_2.5的排放与人口密度、经济水平和气温呈显著正相关,与城市绿化、风速呈显著负相关。该研究为经济增长方式优化、产业结构调整、绿化水平改善等提供了政策建议,可为污染防治、优化人居环境提供参考。     

Combining a road pollution dispersion model with GIS to determine carbon monoxide concentration in Tennessee

The purpose of this paper is to develop an air pollution model that is independent from pollution monitoring sites and highly accurate through space and time. Total carbon monoxide concentration is computed with the use of traffic flow data, vehicle speed and dimensions, emission rates, wind speed, and temperature. The data are interpolated using a geographic information system universal kriging technique, and the end results produce state level air pollution maps with high local accuracy. The model is validated against Environment Protection Agency (EPA) pollution data. Overall, the model has 71 % agreement with EPA, overestimating values of carbon monoxide for less than 1 ppm. The model has three advantages over already assessed air pollution models. First, it is completely independent of any air pollution monitoring stations; thus, possible temporary or permanent unreliability or lack of the data is avoided. Second, being based on a 5,710 traffic count network, the problem of remote places coverage is avoided. Third, it is based on a straightforward equation, where minimal preprocessing of traffic and climatic data is required.     

江苏省机动车排气污染监控体系探讨

机动车保有量的快速发展使得机动车排气污染已成为江苏省城市大气污染的重要来源。开展在用机动车排气污染的防治工作,建立切实有效的机动车排气污染监控体系刻不容缓。对江苏省机动车监控体系和保障体系的建设内容进行了探讨。     

2015—2020年全国重污染天变化趋势及时空分布特征分析

2015—2020年,全国重污染发生天数、比例及城市数量整体呈逐年下降趋势。与2015年相比,2020年全国337个地级及以上城市重污染天数减少1 847 d,降幅达55.2%;重污染天数比例下降1.6个百分点;发生过重污染天气的城市数量减少60个。其中,全国细颗粒物重污染天数整体呈下降趋势,沙尘重污染天数随气象条件的差异波动变化,臭氧重污染天数呈波动上升趋势。"十四五"期间,消除重污染天气的主要对象仍是细颗粒物重污染。应将天山北坡城市群、"2+26"城市、汾渭平原及苏皖鲁豫交界地区作为"十四五"期间污染减排的重点关注区域。此外,需遏制"2+26"城市臭氧重污染上升势头。