Gaseous and particulate emissions from thermal power plants operating on different technologies

This paper presents the assessment of gaseous and particulate emissions from thermal power plants operating on different combustion technologies. Four thermal power plants operating on heavy furnace oil were selected for the study, among which three were based on diesel engine technology, while the fourth plant was based on oil-fired steam turbine technology. The stack emissions were monitored for critical air pollutants carbon monoxide, carbon dioxide, oxides of nitrogen, sulfur dioxide, particulate matter, lead, and mercury. The pollutant emissions were measured at optimum load conditions for a period of 6 months with an interval of 1 month. The results of stack emissions were compared with National Environmental Quality Standards of Pakistan and World Bank guidelines for thermal power plants, and few parameters were found higher than the permissible limits of emissions. It was observed that the emissions carbon monoxide, oxides of nitrogen, and particulate matters from diesel engine-based power plants were comparatively higher than the turbine-based power plants. The emissions of sulfur dioxide were high in all the plants, even the plants with different technologies, which was mainly due to high sulfur contents in fuel.     

Evolution of air pollution in Oporto area

The analysis of pollution data was the support for the proposed remodelation of the network and allowed an estimation of the Air Quality evolution since 1968.The most important pollution sources in Oporto area are the motor traffic, one oil refinery and one petrochemical complex.Strong acidity levels are generally small, but black smoke concentrations are similar to that observed in several European cities.The interpretation of the temporal evolution of network yearly averages, is sometimes not reliable, in consequence of not being possible to get the mean validation of every sites for all years.The network should be increased installing stations in the oldest commercial areas where sulfur dioxide, black smoke, nitrogen oxides, hidrocarbons, carbon monoxide, lead and ozone should be measured. Sulfur dioxide and black smoke should be measured too, in six more areas of the metropolitan Oporto.     

Classification of air quality using fuzzy synthetic multiplication

Proper identification of environment's air quality based on limited observations is an essential task to meet the goals of environmental management. Various classification methods have been used to estimate the change of air quality status and health. However, discrepancies frequently arise from the lack of clear distinction between each air quality, the uncertainty in the quality criteria employed and the vagueness or fuzziness embedded in the decision-making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies when describing integrated air quality conditions with respect to various pollutants. Therefore, this paper presents two fuzzy multiplication synthetic techniques to establish classification of air quality. The fuzzy multiplication technique empowers the max-min operations in "or" and "and" in executing the fuzzy arithmetic operations. Based on a set of air pollutants data carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and particulate matter (PM(10)) collected from a network of 51 stations in Klang Valley, East Malaysia, Sabah, and Sarawak were utilized in this evaluation. The two fuzzy multiplication techniques consistently classified Malaysia's air quality as "good." The findings indicated that the techniques may have successfully harmonized inherent discrepancies and interpret complex conditions. It was demonstrated that fuzzy synthetic multiplication techniques are quite appropriate techniques for air quality management.     

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.     

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。     

Analysis of Urban Atmospheric Pollution Data in the Bologna Area

Pollutant concentrations relative to the years 1993-1995 measured in the Bologna urban area by a network of automatic stations (S.A.R.A. Sistema Automatico di Rilevamento Ambientale) are analysed to estimate the typical behaviour of the pollutants, especially with regard to periodicities and meteorological dependencies and to attempt prediction for the pollutant daily concentration up to a few days using a statistically based model.The results obtained show the presence of a very significant weekly periodicity for all the analysed pollutants. A yearly periodicity has been found only for the primary pollutants analysed.The statistical prediction, using an ARMA model with meteorological variables as transfer functions, shows good predicting capabilities up to one day for carbon monoxide (CO) and sulphur dioxide (SO2) and up to two days for nitrogen dioxide (NO2).     

主分量分析法在环境空气监测数据分析中的应用

根据西宁市13个环境空气监测站点2013—2017年大气污染物细颗粒物(PM2. 5)、可吸入颗粒物(PM10)、二氧化硫(SO_2)、二氧化氮(NO_2)、臭氧最大8 h平均(O_3-8h)和一氧化碳(CO)的监测数据,采用主分量分析法对西宁市环境空气质量进行了综合评估。结果表明,2013—2017年西宁市大部分环境空气监测站点周边环境空气质量逐渐提升,4个国控站综合得分(F)趋势变化幅度较大,其周边环境空气质量状况改善较为明显;城南新区、湟源县气象局和西钢监测站点周边环境空气质量呈逐年下降趋势,与其附近工业生产有关。     

南京市黄标车污染现状与管理对策

以南京市为例,依托机动车环保监管数据库,根据国家机动车排放模型CVEM计算出黄标车主要污染物一氧化碳、碳氢化合物、氮氧化物及颗粒物的年排放量,并系统回顾了近年来为控制黄标车污染所采取的区域限行、淘汰奖补和治理改造等针对性管理措施,分析了政策实施的进展及成效,进一步明确了黄标车治理的必要性。     

Air quality biomonitoring through pollen viability of Fabaceae

In this study, pollen viability and germination of three plant species, Cercis siliquastrum L., Robinia pseudoacacia L., and Spartium junceum L., belonging to the Fabaceae family, was evaluated in sites with different intensity of road traffic, constantly monitored with continuous analysers for air pollutants (carbon monoxide (CO), sulphur dioxide (SO₂), and nitrogen dioxide (NO₂)) by the Municipality of Catania. Two sites, in which road traffic was absent, were selected, too. The percentages of viable pollen by 2,3,5-trypheniltetrazolium chloride (TTC) test ranged from 59.0 to 90.2 % in C. siliquastrum, from 61.5 to 83.5 % in S. junceum and from 67.5 to 84.3 % in R. pseudoacacia. The percentages of germination varied from 41.0 to 72.7 % in C. siliquastrum, from 42.0 to 64.7 % in S. junceum and from 38.3 to 66.3 % in R. pseudoacacia. The highest percentages of viable pollens were found in no-road traffic stations by either TTC or germination tests, while the lowest values were detected in a site characterised by heavy road traffic. In the monitored period (2007–2009), pollen viability, germinability and tube length of C. siliquastrum resulted in a significant negative correlation to CO, SO₂ and NO₂, whereas data from TTC and germination tests on S. junceum and R. pseudoacacia pollens were not well correlated to air pollutants. The results showed that pollen viability, germination and tube growth in C. siliquastrum were affected by air pollution. S. junceum and R. pseudoacacia were not very influenced by air pollutants, suggesting a different pollen sensitivity of these species.     

Urban Air Pollution Patterns, Land Use, and Thermal Landscape: An Examination of the Linkage Using GIS

This article investigates the relationship of local air pollution pattern with urban land use and with urban thermal landscape using a GIS approach. Ambient air quality measurements for sulfur dioxide, nitrogen oxide, carbon monoxide, total suspended particles, and dust level were obtained for Guangzhou City in South China between 1981 and 2000. Landsat TM images and aerial photo derived maps were used to examine city's land use and land cover at different times and changes. Landsat thermal infrared data were employed to compute land surface temperatures and to assess urban thermal patterns. Relationships among the spatial patterns of air pollution, land use, and thermal landscape were sought through GIS and correlation analyses. Results show that the spatial patterns of air pollutants probed were positively correlated with urban built-up density, and with satellite derived land surface temperature values, particularly with measurements taken during the summer. It is suggested that further studies investigate the mechanisms of this linkage, and that remote sensing of air pollution delves into how the energy interacts with the atmosphere and the environment and how sensors see pollutants. Thermal infrared imagery could play a unique role in monitoring and modeling atmospheric pollution.     

Monitoring and Assessment of Exhaust Emission in Bangkok Street Air

Measurement of the exhaust emission from gasoline-powered motor vehicles in Bangkok were performed on chassis dynamometer. A fleet of 10 vehicles of different model, years and manufacturers were selected to measure the air pollutants in the exhaust effluent. The study revealed that the carbon monoxide and hydrocarbon emissions averaged 32.3–64.2 and 1.82–2.98 g km^–1, respectively, for 1990–1992 cars and decreased to 17.8–40.71 and 0.75–1.88 g km^–1, respectively, for 1994–1995 cars. A monitoring program for air pollutant concentrations in ambient air was also conducted to evaluate the air pollution problems in Bangkok arising from vehicle exhaust emission. Four air sampling stations were strategically established to cover the Bangkok Metropolitan Region (BMR). Composite air samples in this study area were collected during the day/night times and weekday/weekend. The average concentrations of suspended particulate matter, carbon monoxide, and nitrogen dioxide in Bangkok street air were found to be 0.65 mg/m³ (24 hr ave.), 19.02 mg/m³ (8 hr ave.) and 0.021 mg/m³ (1 hr ave.), respectively. The average concentrations of benzene and toluene in the ambient air of the study area were found to be 15.07–50.20 and 25.76–130.95 g/mf³, respectively, for 8 hr average. These results indicated that there was a significant increase in air pollutant emissions with increasing car mileage and model year. Subsequent analysis of data showed that there were only 20% of the test vehicles complied to approved emission standard. The finding also revealed that there was a correlation between the average air pollutant concentrations with average traffic speed in each traffic zone of the Bangkok Metropolitan Region (BMR).     

Spatial analysis and land use regression of VOCs and NO2 in Dallas, Texas during two seasons

Passive air sampling for nitrogen dioxide (NO(2)) and select volatile organic compounds (VOCs) was conducted at 24 fire stations and a compliance monitoring site in Dallas, Texas, USA during summer 2006 and winter 2008. This ambient air monitoring network was established to assess intra-urban gradients of air pollutants to evaluate the impact of traffic and urban emissions on air quality. Ambient air monitoring and GIS data from spatially representative fire station sites were collected to assess spatial variability. Pairwise comparisons were conducted on the ambient data from the selected sites based on city section. These weeklong samples yielded NO(2) and benzene levels that were generally higher during the winter than the summer. With respect to the location within the city, the central section of Dallas was generally higher for NO(2) and benzene than north and south. Land use regression (LUR) results revealed spatial gradients in NO(2) and selected VOCs in the central and some northern areas. The process used to select spatially representative sites for air sampling and the results of analyses of coarse- and fine-scale spatial variability of air pollutants on a seasonal basis provide insights to guide future ambient air exposure studies in assessing intra-urban gradients and traffic impacts.     

Seasonal characteristics of SO2, NO2, and CO emissions in and around the Indo-Gangetic Plain

Anthropogenic emissions of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) exert significant influence on local and regional atmospheric chemistry. Temporal and spatial variability of these gases are investigated using surface measurements by the Central Pollution Control Board (India) during 2005–2009 over six urban locations in and around the Indo-Gangetic Plain (IGP) and supported using the satellite measurements of these gases. The stations chosen are Jodhpur (west of IGP), Delhi (central IGP), Kolkata and Durgapur (eastern IGP), Guwahati (east of IGP), and Nagpur (south of IGP). Among the stations studied, SO₂ concentrations are found to be the highest over Kolkata megacity. Elevated levels of NO₂ occur over the IGP stations of Durgapur, Kolkata, and Delhi. Columnar NO₂ values are also found to be elevated over these regions during winter due to high surface concentrations while columnar SO₂ values show a monsoon maximum. Elevated columnar CO over Guwahati during pre-monsoon are attributed to biomass burning. Statistically significant correlations between columnar NO₂ and surface NO₂ obtained for Delhi, Kolkata, and Durgapur along with very low SO₂ to NO₂ ratios (≤0.2) indicate fossil fuel combustion from mobile sources as major contributors to the ambient air over these regions.     

A Simple Model of Pollutant Concentrations in a Street Canyon

A single compartment model has been constructed for predicting hourly concentrations of pollutant concentrations arising from vehicular emissions within a typical street canyon. The model takes account of traffic densities and composition to estimate pollutant emissions within the model compartment. Meteorological data on wind speed and direction are used to define the exchanges of pollutants between the compartment and the surrounding air. A parameter is also included to describe the exchange in calm conditions. The pollutant concentrations are then estimated from a steady state mass balance equation for the compartment, assuming conservation of pollutants. The model was applied to the prediction of carbon monoxide concentrations in Hope Street, Glasgow. Model parameters were fitted using field measurements, together with concurrent meteorological data and traffic flows estimated from traffic census data for Hope Street. The model accounted well for the observed variations in carbon monoxide. It was found that the model parameters varied seasonally, perhaps due to differences in atmospheric stability which have not so far been included in the model formulation.     

A Numerical and Experimental Study of Pollutant Dispersion in a Traffic Tunnel

Three-dimensional turbulent flow and dispersion of gaseous pollutants carbon monoxide (CO) and nitrogen oxides (NOx) in a road tunnel was modeled using the standard k–ε turbulence model and solved numerically using the finite volume method. Vehicle emissions were estimated from the measured traffic flow rates and modeled as banded line sources along the tunnel floor. The effects of fan ventilation and piston effect of moving vehicles on the airflow and pollutant dilution were examined. The numerical results reveal that a peak velocity exists near the tunnel floor due to the piston effect of vehicles. The cross-sectional concentrations of air pollutants are non-uniformly distributed and concentrations rise with downstream distance. The piston effect of vehicles can alone provide 25%–34% dilution of air pollutants in the tunnel, compounded 43%–70% dilution effect according to the ventilation condition.     

Mann–Kendall trend of pollutants,temperature and humidity over an urban station of India with forecast verification using different ARIMA models

The purpose of the present research is to identify the trends in the concentrations of few atmospheric pollutants and meteorological parameters over an urban station Kolkata (22° 32′ N; 88° 20′ E), India, during the period from 2002 to 2011 and subsequently develop models for precise forecast of the concentration of the pollutants and the meteorological parameters over the station Kolkata. The pollutants considered in this study are sulphur dioxide (SO₂), nitrogen dioxide (NO₂), particulates of size 10-μm diameters (PM₁₀), carbon monoxide (CO) and tropospheric ozone (O3). The meteorological parameters considered are the surface temperature and relative humidity. The Mann–Kendall, non-parametric statistical analysis is implemented to observe the trends in the data series of the selected parameters. A time series approach with autoregressive integrated moving average (ARIMA) modelling is used to provide daily forecast of the parameters with precision. ARIMA models of different categories; ARIMA (1, 1, 1), ARIMA (0, 2, 2) and ARIMA (2, 1, 2) are considered and the skill of each model is estimated and compared in forecasting the concentration of the atmospheric pollutants and meteorological parameters. The results of the study reveal that the ARIMA (0, 2, 2) is the best statistical model for forecasting the daily concentration of pollutants as well as the meteorological parameters over Kolkata. The result is validated with the observation of 2012.     

沈阳市冬季环境空气质量统计预报模型建立及应用

利用沈阳市2013年1—2月大气自动监测数据和同期气象资料,选取19项预报因子,采用逐步回归方法建立了沈阳市冬季环境空气质量统计预报模型,预报项目包括细颗粒物(PM2.5)、可吸入颗粒物(PM10)、二氧化硫(SO2)、二氧化氮(NO2)、一氧化碳(CO)日均浓度及臭氧(O3)日最大8 h平均浓度。2013年11月至2014年1月,应用该模型并结合人为经验修订,开展了沈阳市环境空气质量预报工作,预报结果与实测结果的对比验证结果表明,环境空气预测结果级别准确率达到79.1%,首要污染物准确率为73.6%。     

Differences between weekend and weekday ozone levels over rural and urban sites in Southern Italy

Air quality data from a network of 11 monitoring stations in the Apulia region of southern Italy during the summer of 2005 reveal a high frequency of ozone law limit violations. Since ozone is a secondary pollutant, air quality control strategies aimed at reducing ozone concentration are not immediate. Herein, we analyse weekly changes in concentration levels of ozone (O(3)), nitrogen oxides (NO(x)), carbon monoxide (CO), and volatile organic compounds (VOCs), and evaluate how the differences in primary emissions cause changes in the production of ozone. The comparison between weekend and weekday levels of O(3) and its precursors are direct evidence for the existence of the "ozone weekend effect." This effect was observed at all stations with a considerable variation in the overall ozone magnitude, including both traffic stations and non-traffic stations. Data from VOC measurements at traffic stations primarily indicated elevated levels of benzene, toluene, and xylenes (BTX); all of these substances showed an overall decrease over the weekend. A single station indicated levels of non-methane hydrocarbon (NMHC) and PM10, both of which did not demonstrate any weekly cycle. Analysis of weekly and diurnal cycles of O(3), NO(x), CO, NMHC, and PM10 indicates that higher weekend ozone levels result from a reduction in the emission of nitrogen oxides on weekends in VOC-sensitive regimes. This indicates that a reduction in VOC and NO(x) levels would be more effective than NO(x) reduction alone. Our results underscore the need for improved and more efficient VOC measurements.     

Preliminary air pollution monitoring in San Miguel, Buenos Aires

Passive diffusion samplers were employed in San Miguel(Buenos Aires Metropolitan Area) for a preliminary airpollution monitoring. The highest loads were observedin downtown, compared with an urban background site.Total suspended particulate matter (TSPM) varied from0.257 to 0.033 mg cm^-2 month^-1; dust was examinedfor particle nature and size distribution. A similartrend was observed for nitrogen dioxide (NO₂) andTSPM spatial distribution, suggesting that traffic isthe major pollution source. Sulphur dioxide (SO₂)values were low and rather homogeneous. Levels for theinvestigated pollutants are below EPA's guide linevalues. Geographic (flat area, near to Rio de LaPlata) and climatologic factors (rainfalls andvariable wind directions) contribute to disperse pollutants.     

固定污染源废气中三氧化硫测试方法初探

建立了异丙醇吸收-分光光度法测试固定污染源中三氧化硫(SO_3)的方法,分别连续9次测试低、中、高3个质量浓度的SO_3烟气。测试结果表明,相对误差分别为7. 5%,-2. 6%和6. 7%,相对标准偏差分别为3. 3%,1. 7%和4. 1%,方法的准确度和精密度较好。方法检出限为0. 1 mg/m~3,测定下限为0. 4 mg/m~3。二氧化硫(SO_2)、一氧化碳(CO)、氮氧化物(NO_x)、硫化氢(H_2S)、含湿量、烟尘等因素对方法的干扰较小,方法适用于现场测试。