Air quality assessment of Estarreja, an urban industrialized area, in a coastal region of Portugal

Despite the increasing concern given to air quality in urban and industrial areas in recent years, particular emphasis on regulation, control, and reduction of air pollutant emissions is still necessary to fully characterize the chain emissions–air quality–exposure–dose–health effects, for specific sources. The Estarreja region was selected as a case study because it has one of the largest chemical industrial complexes in Portugal that has been recently expanded, together with a growing urban area with an interesting location in the Portuguese coastland and crossed by important road traffic and rail national networks. This work presents the first air quality assessment for the region concerning pollutant emissions and meteorological and air quality monitoring data analysis, over the period 2000–2009. This assessment also includes a detailed investigation and characterization of past air pollution episodes for the most problematic pollutants: ozone and PM10. The contribution of different emission sources and meteorological conditions to these episodes is investigated. The stagnant meteorological conditions associated with local emissions, namely industrial activity and road traffic, are the major contributors to the air quality degradation over the study region. A set of measures to improve air quality—regarding ozone and PM10 levels—is proposed as an air quality management strategy for the study region.     

Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

盐城市空气微生物调查与评价

为了解盐城市空气微生物污染状况,于2009—2013年在盐城市布设了4个城市主要功能区点位和1个市郊清洁参照点,采用自然沉降法采集空气中细菌和马丁霉菌样品进行分析。结果表明,盐城市空气中细菌数量最多的为交通区,其次依次为文教区、工业区、居民区,清洁参照点最少;马丁霉菌数量最多的是交通区,其次依次为工业区、居民区、文教区,清洁参照点最少。盐城市空气微生物污染级别除交通区外,其他功能区均处于较清洁或轻微污染,污染程度呈逐年波动下降趋势。     

Assessing PM10 source reduction in urban agglomerations for air quality compliance

The objective of this work was to study PM(10) and PM(2.5) concentration data available from monitoring stations in two large urban agglomerations in Greece and to estimate the emissions reduction required for compliance with the EU Air Quality Standards (AQS) for particulate matter. The cities studied are namely the Athens and Thessaloniki Metropolitan Areas (AMA and TMA, respectively). PM(10) concentrations during the period 2001-2010 have been evaluated for 15 air quality monitoring stations in the two urban areas. It was found that the concentrations of PM(10) during the period studied constantly exceeded the threshold values at the traffic and industrial stations in TMA and most of the traffic sites in AMA. Most of the occurrences of non-attainment to the daily AQSs were observed during the winter period at all stations (more pronounced for TMA stations). The reduction in current emission source strength to meet the air quality goal was calculated by the rollback equation using PM(10) day-averaged concentrations over the selected period at each station. Among the lognormal and Weibull distributions, the lognormal distribution was found to best fit the frequency distributions of PM(10) concentrations at the selected stations. The results showed that the minimum reduction required in order to meet the AQS in the AMA ranges from approximately 20 to 38% and up to 11% for traffic and background stations, respectively. Reductions in the range of 31% for traffic and 44% for industrial areas in TMA are also required. The same methodology was applied to PM(2.5) concentrations in the AMA and showed that emission reductions up to 31% are necessary in order to meet the 2020 EU AQS. Finally, continuous concentration data of organic (OC) and elementary carbon (EC) in PM(2.5) were used to study the possibility of achieving specific emission attenuation objectives in AMA.     

南京市环境空气中挥发性有机物的组成与特点

参照美国EPATO17的方法研究南京市不同功能区(交通区、商业旅游区、居住区、工业区和清洁对照点)环境空气中挥发性有机物(VOCs)在一年四季中的组成及浓度水平。共检出189种挥发性有机物,并随气温下降而减少;苯系物稳定存在于各功能区,浓度秋季最高。交通区污染最严重。     

Influence of Building Density and Roof Shape on the Wind and Dispersion Characteristics in an Urban Area: A Numerical Study

The Computational Fluid Dynamics code CFX-TASCflow is used for simulating the wind flow and pollutant concentration patterns in two-dimensional wind-tunnel models of an urban area. Several two-dimensional multiple street canyon configurations are studied corresponding to different areal densities and roof shapes. A line source of a tracer gas is placed at the bottom of one street canyon for modelling street-level traffic emissions. The flow fields resulting from the simulations correspond to the patterns observed in street canyons. In particular and in good agreement with observations, a dual vortex system is predicted for a deep flat-roof street canyon configuration, while an even more complex vortex system is evidenced in the case of slanted-roof square street canyons. In agreement with measurement data, high pollutant concentration levels are predicted either on the leeward or the windward side of the street canyon, depending on the geometrical details of the surrounding buildings.     

Preparation and Validation of Gridded Emission Inventory of Criteria Air Pollutants and Identification of Emission Hotspots for Megacity Delhi

Delhi is one of the many megacities struggling with punishing levels of pollution from industrial, residential, and transportation sources. Over the years, pollution abatement in Delhi has become an important constituent of state policies. In the past one decade a lot of policies and regulations have been implemented which have had a noticeable effect on pollution levels. In this context, air quality models provide a powerful tool to study the impact of development plans on the expected air pollution levels and thus aid the regulating and planning authorities in decision-making process. In air quality modeling, emissions in the modeling domain at regular interval are one of the most important inputs. From the annual emission data of over a decade (1990–2000), emission inventory is prepared for the megacity Delhi. Four criteria pollutants namely, CO, SO₂, PM, and NO _x are considered and a gridded emission inventory over Delhi has been prepared taking into account land use pattern, population density, traffic density, industrial areas, etc. A top down approach is used for this purpose. Emission isopleths are drawn and annual emission patterns are discussed mainly for the years 1990, 1996 and 2000. Primary and secondary areas of emission hotspots are identified and emission variations discussed during the study period. Validation of estimated values is desired from the available data. There is a direct relationship of pollution levels and emission strength in a given area. Hence, an attempt has been made to validate the emission inventory for all criteria pollutants by analyzing emissions in various sampling zones with the ambient pollution levels. For validation purpose, the geographical region encompassing the study area (Delhi) has been divided into seven emission zones as per the air quality monitoring stations using Voronoi polygon concept. Dispersion modeling is also used for continuous elevated sources to have the contributing emissions at the ground level to facilitate validation. A good correlation between emission estimates and concentration has been found. Correlation coefficient of 0.82, 0.77, 0.58 and 0.68 for CO, SO₂, PM and NO _x respectively shows a reasonably satisfactory performance of the present estimates.     

工业区恶臭污染自动监控体系设计

选取典型工业区,汇总了恶臭污染的突发性、排放不规律、夜间高值显著等特征,分析了由化学特性、物质种类和监控要求等带来的恶臭污染监测难点。根据信访投诉、地理特点和大气扩散规律,提出构建工业区恶臭污染自动监控体系。在恶臭污染排放特征分析基础上,筛选优控污染物,优选适用在线监测技术,建设边界监控为主、园区监测为辅的专业化、自动化大气特征污染监测系统,通过统一联网和平台,统一质控和规范,建立预警监测信息平台。在实际构建与应用的过程中,探索了分级管理、多方合作的运行机制,为工业区恶臭污染分析评估、污染溯源和控制提供了技术支持。     

盐城市城区VOCs污染特征及来源解析

2020年4—9月通过离线采样研究了盐城市城区大气中的挥发性有机物（VOCs）浓度水平及组成特征、臭氧生成潜势、二次有机气溶胶生成潜势以及毒性效应等多效应评估和来源贡献。结果表明：盐城市城区VOCs平均体积浓度为35.09×10^-9,盐塘湖公园站点浓度最高;盐城市VOCs主要组分为含氧有机物（OVOCs）和烷烃。通过挥发性有机物多效应评估发现,关键物种为乙醛、对二乙苯、丙酮、甲苯和间/对二甲苯等。采样期间对VOCs浓度的主要贡献来源为二次生成、工业排放和交通排放。     

An air quality balance index estimating the total amount of air pollutants at ground level

A new index named Air Quality Balance Index (AQBI), which is able to characterise the amount of pollution level in a selected area, is proposed. This index is a function of the ratios between pollutant concentration values and their standards; it aims at identifying all situations in which there is a possible environmental risk even when several pollutants are below their limit values but air quality is reduced. AQBI is evaluated by using a high-resolution three-dimensional dispersion model: the air concentration for each substance is computed starting from detailed emissions sources: point, line and area emissions hourly modulated. This model is driven with accurate meteorological data from ground stations and remote sensing systems providing vertical profiles of temperature and wind; these data are integrated with wind and temperature profiles at higher altitudes obtained by a Local Area Model. The outputs of the dispersion model are compared with pollutant concentrations provided by measuring stations, in order to recalibrate emission data. A three-dimensional high resolution grid of AQBI data is evaluated for an industrial area close to Alessandria (Northern Italy), assessing air quality and environmental conditions. Performance of AQBI is compared with the Air Quality Index (AQI) developed by the U.S. Environmental Protection Agency. AQBI, computed taking into account all pollutants, is able to point out situations not evidenced by AQI, based on a preset limited number of substances; therefore, AQBI is a good tool for evaluating the air quality either in urban and in industrial areas. The AQBI values at ground level, in selected points, are in agreement with in situ observations.     

Characterizing ozone pollution in a petrochemical industrial area in Beijing,China: a case study using a chemical reaction model

This study selected a petrochemical industrial complex in Beijing, China, to understand the characteristics of surface ozone (O₃) in this industrial area through the on-site measurement campaign during the July–August of 2010 and 2011, and to reveal the response of local O₃ to its precursors’ emissions through the NCAR-Master Mechanism model (NCAR-MM) simulation. Measurement results showed that the O₃ concentration in this industrial area was significantly higher, with the mean daily average of 124.6 μg/m³ and mean daily maximum of 236.8 μg/m³, which are, respectively, 90.9 and 50.6 % higher than those in Beijing urban area. Moreover, the diurnal O₃ peak generally started up early in 11:00–12:00 and usually remained for 5–6 h, greatly different with the normal diurnal pattern of urban O₃. Then, we used NCAR-MM to simulate the average diurnal variation of photochemical O₃ in sunny days of August 2010 in both industrial and urban areas. A good agreement in O₃ diurnal variation pattern and in O₃ relative level was obtained for both areas. For example of O₃ daily maximum, the calculated value in the industrial area was about 51 % higher than in the urban area, while measured value in the industrial area was approximately 60 % higher than in the urban area. Finally, the sensitivity analysis of photochemical O₃ to its precursors was conducted based on a set of VOCs/NOx emissions cases. Simulation results implied that in the industrial area, the response of O₃ to VOCs was negative and to NOx was positive under the current conditions, with the sensitivity coefficients of ?0.16~?0.43 and +0.04~+0.06, respectively. By contrast, the urban area was within the VOCs-limitation regime, where ozone enhancement in response to increasing VOCs emissions and to decreasing NOx emission. So, we think that the VOCs emissions control for this petrochemical industrial complex will increase the potential risk of local ozone pollution aggravation, but will be helpful to inhibit the ozone formation in Beijing urban area through reducing the VOCs transport from the industrial area to the urban area.     

沈阳市环境空气中挥发性有机物污染特征及来源解析

基于2019年沈阳市4个不同功能区挥发性有机物(VOCs)小时分辨率的在线监测数据,分析了环境空气中VOCs的污染特征及来源。结果表明,观测期间沈阳市环境空气中VOCs日平均体积分数为(31.5±13.3)×10~(-9),4个功能区VOCs体积分数均呈现出冬季明显大于夏季的特征;工业区环境空气中VOCs体积分数明显高于其他功能区。商业交通居民混合区、文化居民混合区、郊区VOCs体积分数呈现明显双峰结构,工业区双峰结构不明显。工业区VOCs以新鲜排放为主,而其他3个区域为老化气团的传输。工业区春、夏季环境空气中VOCs来源包括燃料挥发源(26.90%)、溶剂与涂料源(17.69%)、燃烧源(16.40%)、化工源(15.69%)、交通源(7.57%)和炼油炼焦源(4.15%)。秋、冬季VOCs的来源包括燃烧源(30.77%)、溶剂与涂料源(20.26%)、燃料挥发源(18.79%)、化工源(11.54%)、炼油炼焦源(9.34%)和交通源(5.51%)。     

Simulation and Evaluation of Control Strategies for Ozone Reduction in a Complex Terrain in Southwestern Spain

During the central months of the year, southwestern Spain is under strong insolation and weak synoptic forcing, promoting the development of sea breezes and mountain-induced winds and creating recirculations of pollutants. The complex topography of the Southwestern Iberia Peninsula induces the formation of vertical layers, into which the pollutants are injected and subjected to long-distance transport and compensatory subsidence. The characteristics of these highly complex flows have important effects on the pollutant dispersion. Air pollution studies in very complex terrains require high-resolution modelling for resolving the flow dynamics. This paper shows the results obtained from using the MM5-CAMx multiscale-nested air quality model to relate the sensitivity regimes for ozone, nitrogen oxides and volatile organic compounds in an area of high geographical complexity. The article assesses the impact on the hourly and eight-hourly maximum daily ozone concentrations of four reduction strategies during two ozone pollution episodes. This analysis of the ozone response has led to a preliminary evaluation of the effectiveness of the most common control strategies: traffic, industry, mixed traffic and industry, and closure of some of the largest industries (oil and petrochemical refineries). Photochemical indicators show that ozone chemistry in southwestern Spain is strongly sensitive to NO _x . However, volatile organic compound-sensitive points are found in areas with anthropogenic influence (highways, cities and industrial parks). Our results indicate that reductions in road traffic lead to ozone reductions over large areas, whereas reductions in industrial emissions, despite sometimes showing greater decreases in the maximum hourly and eight-hourly ground-level ozone levels, lead to ozone reductions in a local area only. In the control study case, with the oil refinery and the petrochemical plants closed, decreases in ozone hourly concentrations are up to 40% higher than in the other emission control scenarios studied. This analysis provides an assessment of the effectiveness of different policies for controlling precursor emissions by comparing the modelled results for different scenarios.     

Diurnal models of traffic-generated CO for Penang,Malaysia

Georgetown of Penang, an old city, is noted for its narrow streets. The existing traffic dispersal system is utterly inadequate to cope with the ever increasing number of cars and motorcycles on the road. The principal objective of this study is to build prediction models of CO to be employed as one of the planning tools in the future design of Penang urban traffic dispersal system. This study involves the monitoring of kerbside CO levels at selected sites and the fitting of hourly-averaged CO data to linear regression models incorporating the residual effect of CO emission due to traffic in the earlier periods and also different categories of vehicles. The best overall regression model appears to be the one based upon the total traffic count of motorcycles. This can be accounted for by the fact that the traffic counts of motorcycles and cars are highly correlated in most cases and that the emissions of CO from motorcycles are more readily detected as they travel closer to the kerb. The inclusion of residual CO in the models significantly improves the correlation coefficient from about 0.4 to about 0.7.     

The Impact of Road Traffic in Madrid Community by Using a Nested Gaussian-Mesoscale Air Quality Model (GAMA)

In this contribution we show the integration of a mesoscale air quality model OPANA with the ISCST3 Gaussian model (EPA) in order to analyze the impact of different emission sources and particularly the traffic emission into the different gridboxes which define the OPANA Eulerian structure. The application is done over the Madrid (Spain) regional area with 80 × 100 km and gridboxes of about 5 km. Thousands of Gaussian runs over interested gridboxes are executed in order to simulate the traffic emissions from each gridbox. Each mobile unit is represented by a Gaussian point emitter. Input meteorological variables for the ISCST3 are taken from the OPANA mesoscale air quality model. Results shows that it is possible to model the impact of traffic emissions over each gridbox. A short comparison with air quality monitoring in each gridbox is also shown.     

VOCs走航观测在城市污染源排查中的应用

为推进城市空气质量精细化管理工作的实施,实现VOCs污染源精准排查,2019年3-4月,利用单光子电离飞行时间质谱对青岛市重点区域进行了VOCs走航观测。在排查到的污染源中,工业区的VOCs浓度较生活区整体偏高,且生活区、工业区夜间的VOCs浓度均较白天高。VOCs各类组分中,生活区白天苯系物、卤代烃、烯烃、烷烃的占比均在20%左右,夜间苯系物占比明显升高;工业区苯系物在白天和夜间的占比均最高,其他组分相对较小。浓度较高的前10位VOCs物种中,生活区白天烯烃物种占主导,夜间烷烃物种的比重明显增加;工业区苯系物、烯烃物种在白天和夜间的比重均较大,烷烃物种较小。生活区VOCs的污染源主要为机动车尾气排放和油品挥发,工业区主要为企业排放。烯烃和苯系物臭氧生成贡献较烷烃高,特别是丁烯、戊烯、己烯、甲苯、二甲苯/乙苯、三甲苯贡献显著,建议作为优控物种重点管控。     

Variability in Voc Concentrations in an Urban Area of Delhi

The variability of pollutants is an important factor in determining human exposure to the chemicals. This study presents the result of investigation of variability of Volatile organic compounds (VOCs) in urban area of Delhi, capital of India. Fifteen locations, in five categories namely residential, commercial, industrial, traffic intersections and petrol pump were monitored for one year every month during peak hours in morning and evening. Measurement focused on target VOCs as defined by USEPA. Variability was divided into measurement, spatial, temporal and temporal–spatial interaction components. Temporal component along with temporal–spatial interaction were found to be the major contributors to the variability of measured VOC concentrations. Need of continuous monitoring to capture short–term peak concentration and averages is evident.     

环境统计与排污许可衔接的工业源排放核算研究

环境统计面临依据排污许可数据估算工业污染排放总量的挑战.以某市4个行业6类污染物的排放数据为案例,讨论了在非重点源污染排放量估算问题上衔接排污许可和环境统计的可行性和存在的问题.研究结果表明:排污许可重点管理单位与环境统计重点调查单位存在显著差异,不能采用比率估算方法估算工业非重点源排污量;排污许可简化和登记管理单位排...     

基于地基监测的人为源温室气体排放通量反演研究进展

不同尺度下温室气体的空间分布及变化趋势是研究气候变化的基础,也是评估相关减排政策实施效果的重要依据。当前碳排放核算主要基于排放清单,不确定性较大。基于监测数据的碳排放核算能够有效评估和修正排放清单结果,是对当前方法的有效补充。国内温室气体的监测主要针对污染源和环境浓度,对于人为源温室气体排放通量的监测研究较少。该文分析了近年来国内外基于地基监测的人为源温室气体排放通量研究,主要的研究方法可分为2类:柱浓度空间分布结合三维风场数据反演排放通量;结合实测体积分数、大气扩散模型和统计优化模型修正先验排放通量结果,以获取更准确的后验排放通量。通过分析和对比2种方法的优势和局限,讨论不同通量反演方法的适用场景。建议我国未来应构建适用于不同空间尺度的温室气体通量监测反演体系,综合利用多种监测手段,以校核验证排放清单,并为制定温室气体减排策略和评估应对气候变化工作成效提供技术支撑。     

郑州市对流层NO2柱浓度时空变化及其影响因素

基于郑州市2005—2015年的OMI遥感反演资料以及地面相关监测数据,研究了郑州市对流层NO_2的时空分布特征,并利用灰色关联法对郑州市NO_2柱浓度变化的主要影响因素进行分析。与地面观测数据对比检验显示,对流层NO_2柱浓度年均值数据与近地面监测站NO_2浓度的实测年均值数据呈显著的正相关,相关系数分别为0.884 6和0.940 2,表明OMI数据资料可以较好地反映地面NO_2浓度的变化。郑州市的对流层NO_2柱浓度在2005—2013年间呈现波动变化且2013—2015年NO_2柱浓度显著减小的特征。季节变化上NO_2柱浓度主要表现为冬季秋季春季夏季的特点。郑州市对流层NO_2柱浓度的空间变化分布主要表现为由北部向南部逐渐递减的趋势,年际变化上高值区与低值区变化不够显著,中值区近年来不断扩大。灰色关联度分析结果显示,汽车保有量与对流层NO_2柱浓度的灰色关联度最低为0.571,而标准煤消耗量、工业用电量以及采暖供热量与对流层NO_2柱浓度的灰色关联度比较高,分别为0.956、0.828、0.862,即大气中工业过程及采暖期煤炭燃烧排放的NO_2占较大比例,汽车尾气排放所占的比例相对较小。