Development of fuzzy air quality index using soft computing approach

Proper assessment of air quality status in an atmosphere based on limited observations is an essential task for meeting the goals of environmental management. A number of classification methods are available for estimating the changing status of air quality. However, a discrepancy frequently arises from the quality criteria of air employed and vagueness or fuzziness embedded in the decision making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies like air quality index when describing integrated air quality conditions with respect to various pollutants parameters and time of exposure. In recent years, the fuzzy logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental issues. In the present study, a methodology based on fuzzy inference systems (FIS) to assess air quality is proposed. This paper presents a comparative study to assess status of air quality using fuzzy logic technique and that of conventional technique. The findings clearly indicate that the FIS may successfully harmonize inherent discrepancies and interpret complex conditions.     

Cluster analysis of Delhi's ambient air quality data

The purpose of this study was to study the spatial patterns of ambient air quality in Delhi in the absence of extensive datasets needed for space-time modeling. A spatial classification was attempted on the basis of ambient air quality data of nine years (1998 is latest year for which published data were available) for three criteria pollutants--nitrogen dioxide, sulfur dioxide, and suspended particulate matter. Monitoring stations take 24-hour samples twice a week. Published monthly average concentration data were used in this study. A hierarchical agglomerative algorithm using the average linkage between groups method and the Euclidean distance metric was used. Cluster analysis indicated that till 1998, by and large, two distinct classes existed. The results of cluster analysis prompted an investigation of systematic biases in the monitored data. No statistically significant differences in the mean concentration of all pollutants were observed between stations belonging to different land-use types (residential and industrial). This fact would be useful, if and when the authorities consider modifying the network or expanding it in Delhi. The results also support the recommendation that Delhi have a uniform standard across all areas. This study has provided a methodology for Indian researchers and practitioners to do an exploratory study of spatial patterns of air pollution and data quality issues in Indian cities using the National Ambient Air Quality Monitoring System data.     

Proximity analysis of air pollution exposure and its potential risk

Proximity analysis and spatial variability of the ambient nitrogen dioxide (NO(2)) concentration in Rayong province, Thailand, were analyzed using geostatistics and spatial modeling techniques. Annual concentrations of nitrogen dioxide were predicted and spatially interpolated using various interpolation techniques (i.e. kriging, IDW and spline). Sensitivity analysis was carried out to assure the accuracy of the predicted results. The GIS-based exposure map was simulated and was assisted to identify high exposure areas. A health risk warning system was set for "action" (exceeds 100% of the annual average NO(2) guideline), for "alert" (between 66-100% of the annual average NO(2) guideline) and for "some concern" (between 33-66% of the annual average NO(2) guideline). Although no areas were exposed to an action level, many locations in the study area could have levels of "some concern". Potential risk to the population was analyzed by spatial interpolation of the nitrogen dioxide concentration with population data. The result indicated the number of people exposed to air pollution, as well as the areas which have a high risk to air pollution. About 88.3% of the total population in the study area live in areas where levels of air pollution are designated as being in the "some concern" zone. About 6.7% of the registered population have their residence in an area where action should be taken for air quality management. The study demonstrates the application of GIS-based prediction for the evaluation of exposure mapping, in order to determine the spatial extent and frequency of areas where pollution levels exceed target values, and their potential health impacts.     

Air contaminants in a submarine equipped with air independent propulsion

The Swedish Navy has operated submarines equipped with air independent propulsion for two decades. This type of submarine can stay submerged for periods far longer than other non-nuclear submarines are capable of. The air quality during longer periods of submersion has so far not been thoroughly investigated. This study presents results for a number of air quality parameters obtained during more than one week of continuous submerged operation. The measured parameters are pressure, temperature, relative humidity, oxygen, carbon dioxide, hydrogen, formaldehyde and other volatile organic compounds, ozone, nitrogen dioxide, particulate matter and microbiological contaminants. The measurements of airborne particles demonstrate that air pollutants typically occur at a low baseline level due to high air exchange rates and efficient air-cleaning devices. However, short-lived peaks with comparatively high concentrations occur, several of the sources for these have been identified. The concentrations of the pollutants measured in this study do not indicate a build-up of hazardous compounds during eight days of submersion. It is reasonable to assume that a substantial build-up of the investigated contaminants is not likely if the submersion period is prolonged several times, which is the case for modern submarines equipped with air independent propulsion.     

基于韦伯-费希纳拓广定律的环境空气质量标准

基于韦伯--费希纳(Weber-Fischna)定律并加以拓广,指出空气污染物浓度成等比变化时,其对人体和生态环境产生的危害程度成等差变化;应用‘等比赋值,等差分级'的指数标度法,确定出7项空气污染物的日平均浓度的环境空气质量标准,并与国家<环境空气质量标准(GB3095-1996)>进行了比较.结果表明,除NO2、CO和TSP在两种标准中各有一个级别的浓度限值差异稍大外,其余空气污染物的两种标准的相同级别浓度限值十分接近,从而为制订的国家<环境空气质量标准(GB3095-1996)>提供了理论依据.     

Site location optimization of regional air quality monitoring network in China: methodology and case study

Regional air quality monitoring networks (RAQMN) are urgently needed in China due to increasing regional air pollution in city clusters, arising from rapid economic development in recent decades. This paper proposes a methodological framework for site location optimization in designing a RAQMN adapting to air quality management practice in China. The framework utilizes synthetic assessment concentrations developed from simulated data from a regional air quality model in order to simplify the optimal process and to reduce costs. On the basis of analyzing various constraints such as cost and budget, terrain conditions, administrative district, population density and spatial coverage, the framework takes the maximum approximate degree as an optimization objective to achieve site location optimization of a RAQMN. An expert judgment approach was incorporated into the framework to help adjust initial optimization results in order to make the network more practical and representative. A case study was used to demonstrate the application of the framework, indicating that it is feasible to conduct site optimization for a RAQMN design in China. The effects of different combinations of primary and secondary pollutants on site location optimization were investigated. It is suggested that the network design considering both primary and secondary pollutants could better represent regional pollution characteristics and more extensively reflect temporal and spatial variations of regional air quality. The work shown in this study can be used as a reference to guide site location optimization of a RAQMN design in China or other regions of the world.     

喀什市2022年环境空气质量特征分析

为摸清喀什市环境空气质量变化特征,为管理部门进行污染精准管控提供科学参考,基于喀什市2022年环境空气自动监测数据开展分析研究。结果表明:2022年喀什市二氧化硫、二氧化氮、臭氧、一氧化碳年均质量浓度均优于国家二级标准。超标污染物主要为可吸入颗粒物和细颗粒物。喀什市细颗粒物、可吸入颗粒物浓度呈春、秋、冬季高,夏季低的季节特征。     

传感器技术在环境空气监测与污染治理中的应用现状、问题与展望

大气环境污染物监测是建立污染源与环境污染关系的重要技术途径,也是大气综合治理决策所需数据的主要来源。近年来,空气质量精细化管理和污染源精准控制的需求逐渐增长,对监测技术提出了更高的要求。传感器技术作为空气质量监测标准方法的补充,是实现城市空气质量高时空分辨率测量的新手段。研究从传感器的原理及分类入手,通过综述其在环境空气质量监测、污染源监控管理、个人暴露风险评估等领域的应用,总结了传感器技术的研发进展、应用现状和存在问题,并提出其发展方向和前景。     

Air Quality Assessment in Delhi: Before and After CNG as Fuel

A number of policy measures have been activated in India in order to control the levels of air pollutants such as particulate matter, sulphur dioxide (SO₂) and nitrogen dioxide (NO₂). Delhi, which is one of the most polluted cities in the world, is also going through the implementation phase of the control policies. Ambient air quality data monitored during 2000 to 2003, at 10 sites in Delhi, were analyzed to assess the impact of implementation of these measures, specifically fuel change in vehicles. This paper presents the impact of policy measures on ambient air quality levels and also the source apportionment. CO and NO₂ concentration levels in ambient air are found to be associated with the mobile sources. The temporal variation of air quality data shows the significant effect of shift to CNG (Compressed Natural Gas) in vehicles.     

川东北中心城市南充大气污染态势及其主要成因

基于南充市主城区6项大气污染物浓度数据,研究了2014-2020年南充市的空气质量指数、空气质量指数等级和首要污染物的时序分布。结果表明:随着大气污染防治的开展,南充市大气污染物浓度逐渐下降,出现首要污染物的天数逐年减少,空气质量逐步提高。受污染物节律性影响,空气质量呈现明显的季节差异,冬季空气质量最差,春季次之,夏季污染相对较轻,秋季最轻。首要污染物类型的季节分布特征表现为冬季出现首要污染物天数最多,春季和夏季次之,秋季最少。春、秋、冬季以PM_2.5污染为主,夏季以O₃污染为主。从全年来看,与O₃相比,PM_2.5对空气质量的影响更为突出。在持续控制大气污染物排放总量的同时,精细化协同管控细颗粒物、氮氧化物、挥发性有机物和二氧化硫排放将有助于现阶段的大气污染防治。     

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.     

基于AHP的密闭环境空气质量评价模型及其应用

针对指数法在评价密闭环境空气质量中存在评价因素单一,不能反映多种污染物对空气环境质量的综合影响等缺点,结合模糊数学的原理与方法,对密闭环境空气质量进行评价。采用层次分析法赋权,按最大隶属原则,通过模糊数学模型对某密闭环境空气质量进行综合评价,评价结果较科学地反映了空气质量的真实状况。     

Forecasting Air Quality Parameters Using Hybrid Neural Network Modelling

Urban air pollution has emerged as an acute problem in recent years because of its detrimental effects on health and living conditions. The research presented here aims at attaining a better understanding of phenomena associated with atmospheric pollution, and in particular with aerosol particles. The specific goal was to develop a form of air quality modelling which can forecast urban air quality for the next day using airborne pollutant, meteorological and timing variables.Hourly airborne pollutant and meteorological averages collected during the years 1995–1997 were analysed in order to identify air quality episodes having typical and the most probable combinations of air pollutant and meteorological variables. This modelling was done using the Self-Organising Map (SOM) algorithm, Sammon's mapping and fuzzy distance metrics. The clusters of data that were found were characterised by statistics. Several overlapping Multi-Layer Perceptron (MLP) models were then applied to the clustered data, each of which represented one pollution episode. The actual levels for individual pollutants could then be calculated using a combination of the MLP models which were appropriate in that situation.The analysis phase of the modelling gave clear and intuitive results regarding air quality in the area where the data had been collected. The resulting forecast showed that the modelling of gaseous pollutants is more reliable than that of the particles.     

Air quality effects of traffic in a canyon-like street (Falmouth,U.K.)

It has been suggested that in relation to air quality impacts, roads with low (<20 000 vpd) traffic flow need not be consideredas significant. This study examines this suggestion more closelyby comparing real-time monitoring of traffic related pollutants (NO₂, PM₁₀ and PAH) at two sites (including a `canyon-street') in Falmouth, Cornwall in relation to traffic flow. For comparison, real-time monitoring data for NO₂ and PM₁₀ is also taken from a well ventilated site in Camelford, Cornwall. The data obtained suggest that roads with traffic flow considerably lower than 20 000 vpd can give rise topollutant levels which have implications for human health. The application of simple linear regression techniques to the datasuggests that under certain conditions simple estimates can be made in relation to likely traffic-related air quality effects in canyon-like streets.     

空气质量多模式预报系统在中山市的应用

介绍了中山市空气质量多模式预报系统。对2015年3月—2016年2月的预报效果评估表明:系统可以较好地反映污染物的变化趋势但仍存在系统性偏差。通过对排放源清单的调整优化及对模式干沉降模块的改进使模式系统的偏差显著减小。总结并建立中山市污染天气案例库,发现在典型污染天气形势下,除O3-8 h外,其他污染物均值均能达到空气质量二级标准。未来将从2个方面提高中山市空气质量预报预警系统的实用性,包括逐步实现污染源排放清单的动态及时更新和提高极端气象条件下O3污染预报能力。     

基于区域环境空气质量和碳排放数据的减污降碳协同效果评估

化石燃料燃烧产生的温室气体与大气污染物具有同根同源性,但具体治理中减污降碳的协同效果尚不明确。以浙江省11个设区市为研究样本,对环境空气质量和二氧化碳(CO₂)排放数据进行分析研究,结果显示：2016—2020年浙江省环境空气质量持续改善,但CO₂排放总量仍处于增长阶段。11个设区城市PM_2.5年均浓度降幅在26%～41%之间,二氧化氮(NO₂)年均浓度下降趋势不明显,大部分城市呈现碳排放增加、NO₂浓度下降的特征,只有杭州和温州两市呈现碳排放总量和NO₂、PM_2.5浓度协同下降的趋势。因子相关性分析结果表明,各设区市呈现NO₂浓度与碳排放相关性较大、协同性强,PM_2.5浓度与碳排放相关性较小的特点。进一步通过减污降碳协同定量评价分析表明,浙江地区在环境空气质量改善和温室气体减排已表现出一定成效,但各设区市因产业结构、环境基础条件、协同程度等不同导致减污降碳综合绩效有明显差异。从源头减排实现...     

对比分析法在环境空气质量预报业务中的应用

通过分析京津冀及周边区域环境空气质量预报的实际案例,从实时监测、污染源、大气条件以及数值预报模拟4个方面阐述了对比分析法在空气质量预报业务中的应用,帮助预报员比较类似污染源排放条件下的大气条件变化或者类似大气条件下的污染源变化,以便进一步开展量化分析。研究结果显示:利用时间同比、空间比较和大气条件对比的分析方法,能够判断在类似污染源排放和相似大气条件下,主要污染物的浓度水平、重污染发生、影响范围、持续时间、严重程度等污染特征以及污染物的水平传输影响等;采用污染源变化对比分析法,能够获得在类似大气条件下,污染源排放的减少或剧增对主要污染物浓度水平的影响程度;通过数值预报模式结果对比分析,能够获得在类似的污染源排放条件下,大气环流形势的稳定程度和变化情况,从而判断其对污染物浓度水平的影响。对比分析法是开展京津冀及周边区域环境空气质量预报业务中的重要环节,有利于持续提高空气质量预报的准确率,供全国空气质量预报员开展辖区空气质量预报时参考。     

Photochemical pollution indicators—an analysis of 12 European monitoring stations

Indicators were devised to classify air pollution monitoring sites according to the type of expected photochemical pollution. The indicators are based on measured ozone volume fractions, the most frequently monitored component of photochemical pollution, and in particular on two contributions: one due to the ratio of daily maximum-to-minimum ozone volume fractions and the other to observed peak values. The two contributions regarded as independent are logically connected by “and” and therefore mathematically combined by multiplication. The criterion of classification is mainly described by the mentioned ratio and incidences of ozone volume fractions exceeding the limit of 80 ppb. Twelve monitoring stations within the European network (Cooperative programme for monitoring and evaluation of long-range transmission of air pollutants in Europe, EMEP) were classified according to this indicator predicting what ozone levels can be expected at the particular sites during the growth season (April through September) into three groups: clean, medium, and polluted, based on the data for the 7 years (1997 to 2003).     

Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

Assessment of the Status of Urban Air pollution And Its Impact on Human Health in the City of Kolkata

Air pollution has significant effects on exacerbation of asthma, allergy and other respiratory diseases. Like many other magacities in the world the ambient air quality of Kolkata is also being deteriorated day by day. Automobile exhausts and certain industrial pollutants produce O₃ by photochemical reactions. The particulate matter, particularly less than 10 μ in size, can pass through the natural protective mechanism of human respiratory system and plays an important role in genesis and augmentation of allergic disorders. Sources of air pollution in the area and the unique problem arising out of the emission from the vehicles, industries, etc. have been described. Ambient air quality was monitored along with micrometeorological data and the results are discussed. The status of air pollution in the area has been evaluated and a questionnaire survey was conducted to estimate the allergic symptoms and exposure to assess the respiratory disorders. The data are analysed to evaluate the critical situation arising out of the emission of air pollutants and the impact on human health due to respirable diseases (RDs) to middle class sub-population (activity-wise) in the area are assessed. A strategic air quality management plan has been proposed. For the mitigation of air pollution problems in the city, the different measures to be adopted to maintain the balance between sustainable development and environmental management have been discussed.