“十一五”时期乌鲁木齐市大气污染特征及影响因素分析

为全面了解\"十一五\"时期(2006—2010年)乌鲁木齐市大气污染状况,评估污染源治理及气象条件对空气质量变化的影响,利用2001年1月—2010年12月主要大气污染物浓度数据和同期地面气象资料,总结\"十一五\"时期乌鲁木齐市大气污染变化特征,重点分析其变化原因。结果表明:\"十一五\"时期PM10和SO2年均浓度分别比\"十五\"下降1.7%和10.3%,采暖季降幅最明显,分别达到2.2%和21.9%;而NO2年均浓度比\"十五\"升高8.9%,非采暖季增幅最大,为11.7%。2006—2010年PM10、SO2年均浓度整体呈下降趋势,NO2浓度有升高趋势。5年中非采暖季各污染物浓度均达标,采暖季PM10和SO2超标倍数逐年减小,煤烟型污染特征仍然典型。污染源管控(特别是减排工程实施)是\"十一五\"时期SO2和PM10浓度下降的重要原因,气象条件作用相对有限。NO2浓度升高主要与机动车保有量逐年增加和氮氧化物治理启动滞后有关。     

2018年长三角一次持续重污染过程分析

利用常州市6个环境空气质量评价点PM_2.5、PM₁₀、SO₂、NO₂、CO和水溶性离子数据,结合后向轨迹、激光雷达探空资料、气象资料等,分析了2018年1月29日—2月2日长三角区域一次持续重污染过程。结果表明,重度污染时次高达94 h,PM_2.5最高值达235 μg/m³,由外来输送污染物与本地排放的污染物叠加而成,在不利气象条件影响下,污染物在长三角区域长时间滞留;重污染期间,污染物日变化规律显示,PM_2.5受外来源影响更显著,而SO₂、NO₂受本地污染源影响更显著,水溶性粒子组分与常州市本地源存在较大差异,其中NO₃^-、NH₄⁺、K⁺、Mg²⁺和SO₄^2-值增加最为明显,较污染前分别增加了9.1,5.9,4.3,4.2和4.1倍;K⁺值升高较快,说明污染期间也受到了生物质燃烧的影响。此外,NO₃^-和SO₄^2-在空气质量较好时,在水溶性离子中的占比日变化幅度较大,而在重污染期间,NO₃^-和SO₄^2-日变化幅度明显减小。     

Study of urban atmospheric pollution in Navarre (Northern Spain)

An ambient air quality study was undertaken in two cities (Pamplona and Alsasua) of the Province of Navarre in northern Spain from July 2001 to June 2004. The data were obtained from two urban monitoring sites. At both monitoring sites, ambient levels of ozone, NO_x, and SO₂ were measured. Simultaneously with levels of PM₁₀ measured at Alsasua (using a laser particle counter), PM₁₀ levels were also determined at Pamplona (using a beta attenuation monitor). Mean annual PM₁₀ concentrations in Pamplona and Alsasua reached 30 and 28 μg m⁻³, respectively. These concentrations are typical for urban background sites in Northern Spain. By using meteorological information and back trajectories, it was found that the number of exceedances of the daily PM₁₀ limit as well as the PM₁₀ temporal variation was highly influenced by air masses from North Africa. Although North African transport was observed on only 9% of the days, it contributed the highest observed PM₁₀ levels. Transport from the Atlantic Ocean was observed on 68% of the days; transport from Europe on 13%; low transport and local influences on 7%; and transport from the Mediterranean region on 3% of the days. The mean O₃ concentrations were 45 and 55 μg m⁻³ in Pamplona and Alsasua, respectively, which were above the values reported for the main Spanish cities. The mean NO and NO₂ levels were very similar in both sites (12 and 26 μg m⁻³, respectively). Mean SO₂ levels were 8 μg m⁻³ in Pamplona and 5 μg m⁻³ in Alsasua. Hourly levels of PM₁₀, NO and NO₂ showed similar variations with the typically two coincident maximums during traffic rush hours demonstrating a major anthropogenic origin of PM₁₀, in spite of the sporadic dust outbreaks.     

Distribution of PM2.5 and PM10-2.5 in PM10 Fraction in Ambient Air Due to Vehicular Pollution in Kolkata Megacity

This research paper aims at establishing baseline PM₁₀ and PM_2.5 concentration levels, which could be effectively used to develop and upgrade the standards in air pollution in developing countries. The relative contribution of fine fractions (PM_2.5) and coarser fractions (PM_10-2.5) to PM₁₀ fractions were investigates in a megacity which is overcrowded and congested due to lack of road network and deteriorated air quality because of vehicular pollution. The present study was carried out during the winter of 2002. The average 24h PM₁₀ concentration was 304 μg/m³, which is 3 times more than the Indian National Ambient Air Quality Standards (NAAQS) and higher PM₁₀ concentration was due to fine fraction (PM_2.5) released by vehicular exhaust. The 24h average PM_2.5 concentration was found 179 μg/m³, which is exceeded USEPA and EU standards of 65 and 50 μg/m³ respectively for the winter. India does not have any PM_2.5 standards. The 24 h average PM_10-2.5 concentrations were found 126 μg/m³. The PM_2.5 constituted more than 59% of PM₁₀ and whereas PM₁₀-PM_2.5 fractions constituted 41% of PM₁₀. The correlation between PM₁₀ and PM_2.5 was found higher as PM_2.5 comprised major proportion of PM₁₀ fractions contributed by vehicular emissions.     

Air Pollution Concentrations of PM2.5, PM10 and NO2 at Ambient and Kerbsite and Their Correlation in Metro City – Mumbai

Ambient concentrations of PM_2.5 and PM₁₀ are of concern with respect to effects on human health and environment. Increased levels of mortality and morbidity have been associated with respirable particulate air pollution. In India, it is not yet mandatory to monitor PM_2.5 levels therefore very limited information is available on PM_2.5 levels. To understand the fine particle pollution and also correlate with PM₁₀ which are monitored regularly in compliance with ambient air quality standards. This study was carried out to monitor PM_2.5, PM₁₀, and NO₂ for about one year in a residential cum commercial area of Mumbai city with a view to understand their correlation. The average PM_2.5 concentration at ambient and Kerbsite was 43 and 69 μg/m³. The correlation coefficients between PM_2.5 and PM₁₀ at ambient and Kerbsite were 0.83 and 0.85 respectively thus indicating that most of the PM_2.5 and PM₁₀ are from similar sources. TSP, PM₁₀ levels exceeded Central Pollution Control Board(CPCB) standard during winter season. PM_2.5 levels also exceeded 24 hourly average USEPA standard during winter season indicating unhealthy air quality.     

Assessment of Air Quality After the Implementation of Compressed Natural Gas (CNG) as Fuel in Public Transport in Delhi, India

Public transport in Delhi was amended by the Supreme Court of India to use Compressed Natural Gas (CNG) instead of diesel or petrol. After the implementation of CNG since April 2001, Delhi has the highest fraction of CNG-run public vehicles in the world and most of them were introduced within 20 months. In the present study, the concentrations of various criteria air pollutants (SPM, PM₁₀, CO, SO₂ and NO_x) and organic pollutants such as benzene, toluene, xylene (BTX) and polycyclic aromatic hydrocarbons (PAHs) were assessed before and after the implementation of CNG. A decreasing trend was found for PAHs, SO₂ and CO concentrations, while the NO_x level was increased in comparison to those before the implementation of CNG. Further, SPM, PM₁₀, and BTX concentrations showed no significant change after the implementation of CNG. However, the BTX concentration demonstrated a clear relation with the benzene content of gasoline. In addition to the impact of the introduction of CNG the daily variation in PAHs levels was also studied and the PAHs concentrations were observed to be relatively high between 10 pm to 6 am, which gives a proof of a relation with the limited day entry and movement of heavy vehicles in Delhi.     

佛山市高明区环境空气污染物变化分析

根据佛山市高明区2007—2012年环境空气监测数据资料,分析该区近6年来空气污染物的变化趋势和影响因素。结果表明,2007—2012年该区空气污染呈现由单一型污染向复合型污染转变,综合污染指数总体上升,污染物以SO2、PM10为主。SO2、NO2浓度呈逐年增长,PM10则呈平稳状态。三者污染浓度最高值均在每年第4季度出现。该区的SO2浓度主要受工业污染源影响;NO2也受工业影响显著,与机动车数量呈正相关;PM10与烟粉尘排放量呈正相关,与降水量呈负相关。因此,改善该区环境空气应着重从控制工业污染源、扬尘污染、机动车排气污染3大方面开展工作。     

2001年~2008年及奥运会期间天津市大气污染特征分析

根据天津市大气质量监测数据,对2001年～2008年及奥运会期间天津市大气污染特征和主要大气污染物的变化规律进行了分析。结果表明,2001年～2008年天津市的PM10、SO2和NO2污染总体呈下降趋势,但质量浓度仍相对较高。2008年8月奥运会期间天津市PM10和SO2质量浓度达到国家空气质量二级标准,NO2质量浓度达到国家空气质量一级标准,空气质量良好。天津市PM10污染相对稳定,SO2和NO2的污染分布呈现明显的季节性,时间上表现为冬强夏弱。气象条件对污染物浓度影响明显,沙尘、大雾等天气可使污染物浓度急剧升高。     

Ambient Air Quality Status in Raniganj-Asansol Area, India

This investigation presents the assessment of ambient air quality with respect to suspended particulate matter (SPM), sulphur dioxide (SO₂) and oxides of nitrogen (NO_X) at four sites (RGC, SRS, BBC and BCC) in the Raniganj-Asansol area in West Bengal, India. Ambient air was monitored with a sampling frequency of twenty four hours (3 × 8 hours) at each site on every alternate day (3 days a week) covering a period of one year. A total of 429 samples were collected from RGC, 429 from SRS and 435 each from the BBC and BCC sites. Meteorological parameters such as temperature, relative humidity, wind-speed and wind-direction were also recorded simultaneously during the sampling period. Monthly and seasonal variation of these pollutants have been observed and recorded. The annual average and range values have also been calculated. Results of the investigation indicates that the 95th percentile values of SPM levels exceed the limits (200 g m^-3) at RGC, SRS and BBC sites and is within the limit of 500 g m^-3 at the BCC sites. The 95th percentile values of SO₂ levels did not exceed the reference level at any of the monitoring stations. The 95th percentile values of NO_X are found to be exceeding the limit (80 g m^-3) at RGC, SRS and BBC sites but is within the prescribed limit of 120 g m^-3 at the BCC site. Further, it has been observed that the concentrations of the pollutants are high in winter in comparison to the summer or the monsoon seasons. Results of the investigation indicates that industrial activities, indiscriminate open air burning of coal by the local inhabitants for cooking as well as coking purposes, vehicular traffic, etc. are responsible for the high concentration of pollutants in this area.     

Monitoring of Criteria Air Pollutants in Bursa, Turkey

The concentrations of criteria air pollutants such as CO, NO_x (NO + NO₂), SO₂ and PM were measured in the period of May 2001 and April 2003 in the city of Bursa, Turkey. The average concentrations for this period were 1115±1600 μg/m³, 29±50 μg/m³, 51±24 μg/m³, 79±65 μg/m³, 40±35 μg/m³, 98±220 μg/m³, for CO, NO, NO₂, NO_x, SO₂ and PM, respectively. Temporal changes in concentrations were analyzed using meteorological factors. Correlations among pollutant concentrations and meteorological parameters showed weak relations nearly in all data. Lower concentrations were observed in the summer months while higher concentrations were measured in the winter months. The increase in winter concentrations was probably due to residential heating. Pollutants were associated with each other in order to have information about their origin. NO_x/SO₂ ratio was also examined to bring out the source origin contributing on air pollution (i.e., traffic or stationary).     

Extension of the EUROS Integrated Air Quality Model to Fine Particulate Matter by Coupling to CACM/MADRID 2

The European Operational Smog (EUROS) integrated air quality modelling system has been extended to model fine particulate matter (PM). From an extended literature study, the Caltech Atmospheric Chemistry Mechanism and the Model of Aerosol Dynamics, Reaction, Ionisation and Dissolution were selected and recently coupled to EUROS. Currently, modelling of mass and chemical composition of aerosols in two size fractions (PM_2.5 and PM_10–2.5) is possible. The chemical composition is expressed in terms of seven components: ammonium, nitrate, sulphate, elementary carbon, primary inorganic compounds, primary organic compounds and secondary organic compounds. Calculated PM₁₀ concentrations and chemical composition are presented for two summer months of the year 2003 (1 July to 31 August).     

RELEVANT ASPECTS OF AIR QUALITY IN OPORTO (PORTUGAL): PM10 AND O3

The air quality Framework Directive (FWD) and the correspondent Daughter Directives defined the new strategy for air quality management in Europe. In general, the new standards are more restrictive than those established by the previous legislation. In Portugal, some difficulties can be previewed to achieve those new standards. Thus, this paper aims at evaluating the impact of application of the FWD to Oporto Metropolitan Area in what concerns to the most critical air pollutants in the area (PM₁₀ and O₃). The specific objectives were: i) to analyse the concentration exceedances between 1999 and 2001; ii) to identify the main emission sources; iii) to evaluate the possibility of a new redistribution of the existing monitoring sites; iv) to contribute to the definition of a new strategy for air quality management. The results showed that; i) the standard values for PM₁₀ and O₃ were largely surpassed, possibly concluding that the FWD application implies a strong impact on the air quality management strategies; ii) the main emission sources (road traffic and the neighbour stationary sources localised upwind) affect all the Metropolitan area through intra-region pollutant transport; iii) it is safer maintaining the site localisation to avoid previewing exceedances through mathematical correlations; iv) the reduction of PM₁₀ and of ozone precursors must be performed considering new technologies for cleaner production and gaseous depuration, a rigorous urban and territory planning, the creation of an efficient public transport network and the definition of strict measures for car maintenance.     

Variation in spatial pattern of criteria air pollutants before and during initial rain of monsoon

Spatial patterns of various criteria air pollutants,like SO₂, NO₂, O₃, and TSP were studied atShahdara National Ambient Air Quality Monitoring stationin Delhi (India) in July 1999. The minimum pollutantconcentrations were observed during morning hours,whereas the highest concentrations were found during thelate night hours, which seem to be related with thevehicular emission. Pre-monsoon daily ambient airquality spatial pattern was compared with the spatialpattern during initial and subsequent rain shower ofmonsoon. These spatial patterns were found to beessentially the same before and during rain, however asignificant decrease in SO₂, NO₂ and TSPconcentrations (40-45%) was observed after initial andsubsequent rains of the monsoon, demonstrating theimportance of rainfall in the scavenging of thesecriteria air pollutants.     

Spatio-Temporal Variations of Sulphur Dioxide Patterns with Wind Conditions in Central Taiwan

Sulphur dioxide (SO₂) is one of the main atmospheric pollutants in central Taiwan. This article analyses the SO₂ concentration seasonal variations and spatial distribution using data obtained from ten air quality monitoring stations and the Taiwan Weather Bureau. It reveals that SO₂ concentration is high in winter and low in summer and that high concentration centers are located south of the Taichung coal-fired power plant, the main source of SO₂ emissions in the region.The location of high concentration centers changeswith different prevailing winds. SO₂ variations due towind direction are not unique. During short periods,when meteorological conditions are constant, variationin the pollution sources cause variations in thespatial distribution. This has been deduced byappreciation of Intervention analysis to time seriesof hourly data.     

Integration of Remote Sensed and In-situ Data in an Analysis of the Air Pollution Effects on Terrestrial Ecosystems in the Border Areas between Norway and Russia

Transboundary air pollution from industries in Nikel and Zapolyarnij has caused severe damage to the environment in Southern-Varanger in Norway and in Pechenga municipality in Russia. The work presented in this paper focuses on the integration of in-situ air pollution data with remote sensing based land cover maps. Land cover maps have been utilised to detect changes in the major land cover types within the area. The major change in the environment was the decrease of the sensitive lichen-dominated land cover types, and the increase of bilberry-dominated land cover types and finally the increase of the land cover types with the greatest air pollution stress (industrial barren, barren, and partly damaged vegetation, defoliated forests, lichen removal). A GIS based method for assessing the relationship of the remotely sensed land cover maps with the environmental condition parameters was developed and applied. By comparing the results from this analysis we observed that the land cover types with the greatest stress had the largest concentrations of SO₂ in the ground air layer, while the land cover types with minor damage (the remaining lichen-dominated vegetation) had rather low concentrations of sulphur dioxide in the ground air layer. The area of the land cover types with the greatest stress (industrial barren, barren and partly damaged vegetation) has increased in the period 1973–1988, and the degradation is carried out in a such manner that sensitive mountain and lichen vegetation formations have been transformed into a more barren-like environment. The increase in the emissions has also transferred the natural barrens which also consisted of some sparse vegetation into a complete barren with little vegetation left. Also the epilitic lichens and mosses on bare rocks and stones were also removed by the high concentrations of SO₂. The land cover types with minor damage (with the remaining lichen-dominated vegetation) had rather low concentrations of the contaminants (SO₂, Ni and S), while the partly damaged and damaged land cover types had the highest concentrations of the contaminants. An exception was the Ni and S concentrations found in class 11 Industrial barrens which were lower than expected. Associations between the degradation and the SO₂ concentration in the air were also documented. The conclusion from this analysis is that the in-situ data support the observations of damaged vegetation and industrial barrens imaged by the Landsat satellites, especially in the surroundings of Nikel and Zapolyarnij.     

Assessment of Ambient Air Quality in Urban Centres of Haryana (India) in Relation to Different Anthropogenic Activities and Health Risks

Considering the mounting evidences of the effects of air pollution on health, the present study was undertaken to assess the ambient air quality status in the fast growing urban centres of Haryana state, India. The samples were collected for total suspended particulate matter (TSPM), respirable suspended particulate matter (PM₁₀), sulfur dioxide (SO₂), and oxides of nitrogen (NO₂) during different seasons from 8 districts of Haryana during January, 1999 to September, 2000. The four types of sampling sites with different anthropogenic activities i.e. residential, sensitive, commercial and industrial were identified in each city. The ambient air concentration of TSPM and PM₁₀ observed was well above the prescribed standards at almost all the sites. The average ambient air concentrations of SO₂ and NO₂ were found below the permissible limits at all the centres. Comparatively higher concentration of SO₂ was observed during winter seasons, which seems to be related with the enhanced combustion of fuel for space heating and relatively stable atmospheric conditions. Air Quality Index (AQI) prepared for these cities shows that residential, sensitive and commercial areas were moderately to severely polluted which is a cause of concern for the residents of these cities. The high levels of TSPM and SO₂ especially in winter are of major health concern because of their synergistic action. The data from Hisar city reveals a significant increase in the total number of hospital visits/admissions of the patients with acute respiratory diseases during winter season when the level of air pollutants was high.     

Monitoring of Particle Mass and Number in Urban Air

Measurements of aerosol particles in the air of an urban area in the UK have been made. Ambient air was sampled and the particulates measured after passing through a size selective PM₁₀ inlet. Particle mass was measured using a Tapered Element Oscillating Microbalance (TEOM). Particle number and size distributions were obtained using an Electrical Aerosol Analyser (EAA) and an Aerodynamic Particle Sizer (APS). Measurements were also made of local meteorological parameters. Fine particle number concentrations were found to show better temporal agreement, including diurnal variation, with particle mass concentrations than the coarser particle number concentrations.     

能源结构变化对兰州市大气质量的影响

将2001—2010年的主要能源材料消耗、主要污染物变化及主要行业分布进行了相关性分析,结果表明:兰州市大气4种主要污染物中除烟尘呈下降趋势外,废气总量、SO2、NOx仍呈上升趋势;主要污染源为燃煤,主要污染行业为电力、蒸汽热水产供业;废气和SO2排放总量与燃煤和燃气呈强正相关,而NOx排放只与燃气呈强正相关。建议发挥兰州地域优势,加大以水电供应为主的能源结构调整,对改善当地空气质量有重要价值。     

Inter-Laboratory Comparison of No2 and SO2 Generated by Dynamic Dilution System Under Laboratory Conditions: A Technical Discussion

A workshop on analytical quality control (AQC) of ambient air quality measurement methods for nitrogen dioxide (NO₂) and sulphur dioxide (SO₂) was conducted by Central Pollution Control Board (CPCB) for officials involved in National Ambient Air Quality Monitoring (NAAQM) in India. Concentrations of NO₂ and SO₂ were generated by dynamic dilution system under laboratory conditions at low and high levels and measured using static dilution system and wet chemical methods laid down by CPCB under section 16(2)(h) of the air act 1981. CPCB provided the measured values as reference values for comparing the means obtained by the officials participated from thirteen organizations. A tolerance limit of ±15% of the reference values was specified to accept the results. Generated concentrations, which were unknown to the participants, were measured using gaseous sampling assembly (Envirotech APM 411, New Delhi, India), and wet chemical methods laid down by CPCB i.e. the same methodology which is used by the organizations to generate the data of NO₂ and SO₂ in ambient air. Simultaneously, concentrations were checked by CPCB using automatic analyzers as a check on reference concentration. It is observed that results of automatic analyzers for NO₂ and SO₂ were within a tolerance of ±5% with %RSD below 3. On the other hand, results of most of the participants showed variability in the measurements with %RSD ranging between ±0.8 and ±88.6 and exceedences of means from the tolerance limit with bias ranging between 1.4 and −59%. To check the cause of high variability in the measurements obtained under identical conditions, duplicate sampling was performed by one of the participants for SO₂ at low concentration level. In this study, results of wet chemical methods, automatic analyzers and results of duplicate sampling are analysed statistically to assess the cause of high variability in the measurements. Analysis of t-test and analysis of variance (ANOVA) showed highly significant results for NO₂ and SO₂ at high concentration levels (α 0.05) and for SO₂ at both the levels (α 0.01) respectively indicating some bias is existing either in the sampling or in analytical technique. Duplicate sampling performed to check precision in parallel measurements showed high %RSD indicating the presence of systematic error in sampling technique as the same calibration factor (CF) was used to measure the concentration of duplicate samples. Statistical analysis of flow rates of duplicate sampling showed that the sampling assembly could not maintain the constant flow rate within the ±10% with that measured at the start of the sampling. This resulted in high %RSD and deviation from the reference values for the results of most of the participants, even after accepting ±15% tolerance limit. There is a need to improve and evaluate this gaseous sample collection device under laboratory conditions to generate reliable database of NO₂ and SO₂ in ambient air.     

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.