The third dimension in the Los Angeles basin

Airborne measurements were made during the summer and early fall seasons of 1978–1980 to characterize the third dimension of the Los Angeles Basin during air pollution days. One to three aircraft were employed per flight day to measure the vertical profile of meteorology and air quality continuously, and to collect aerosol samples for the various chemical analyses across the Basin. Particular emphasis was placed in the nighttime measurements. This was done because relatively little nighttime third dimension data are available to date, and because they are important in defining the initial conditions for the following photochemically active days. It was found that the physical and chemical characteristics within the two meteorological regimes, i.e., mixed and stable layers, are distinctively different. The mixed layer is characterized by uniformly low O₃ and relatively high NO_x at night, while he stable layer has stratified high O₃ but low NO_x. Aerosol size distribution in the mixed layer is found to be tri-modal, while that in the stable layer is nearly bi-modal. Based on the collected data, the nighttime sulfur, nitrate and ammonia chemistry is discussed.     

Assessing air quality in Hong Kong: A proposed,revised air pollution index (API)

The Environment Protection Department of Hong Kong has been using an air pollution index (API) to report the status of ambient air quality since 1995. Such an index system was first developed by the USA Environmental Protection Authority. The API compares five main air pollutants, i.e. sulfur dioxide (SO₂), respirable suspended particulates (RSP), nitrogen dioxide (NO₂), carbon monoxide (CO) and Ozone (O₃) as sub-indexes, which are calculated separately from a segmented linear function that transforms ambient pollutants concentrations into a normalized scale extending from 0 to 500. The resultant pollution level is described by the maximal value of these five sub-indexes. The limitation of this API system is that it considers only one pollutant with the maximum value at a time but reflects other pollutants concurrently. In this study, a revised air quality index (RAPI) is proposed based on the entropy function, which combines the effect of all pollutants on public health. The design of the revised index is based on database of air pollutants collected at two air quality monitoring stations in Hong Kong, i.e. a roadside station in Mong Kok and a general station in Sha Tin. Compared with the existing API, values of RAPI (calculated from data collected for API) at both stations are at higher levels and provide more information of levels of all pollutants. Therefore, RAPI should be representatively and widely used to provide the public with a better indicator of air quality. In addition, variations and oscillations of pollutants concentrations were also examined and the results show that RSP and NO₂ contribute more to the overall pollution level than other components. It is suggested that more abatement strategies be focused on these pollutants to improve air quality in the future.     

美国大气污染控制装置市场的分析(Ⅲ)

2.2.2.2电除尘器销售额增长速度缓慢,市场发展速度适中在八十年代中,电除尘器市场的增长速度比较缓慢,其销售额从1981年的1.15亿美元,增加到1986年的3.96亿美元,6年间增加了两倍多。到1986年,在所有大气污染控制装置中,电除尘器的销售额仅次于袋滤器,居第二位。自本世纪初电除尘器应用于工业以来,在电除尘器的理     

Characterization of ozone precursor volatile organic compounds in urban atmospheres and around the petrochemical industry in the Tarragona region

This paper reports the results of an assessment of volatile organic compound (VOCs) levels in ambient air in samples collected at urban and industrial sites in southern Catalonia, which is home to one of the most important petrochemical complexes in southern Europe. This study contains data from a total of 192 samples collected in 2007, from May to October, at six air pollution measurement stations within the area of influence of several chemical and petrochemical industrial plants. The ambient air concentrations of a group of 65 VOCs, some of them ozone precursors, were determined by active sampling into sorbent tubes, thermal desorption and gas chromatography-mass spectrometry. At the same time, several meteorological parameters were also recorded, and levels of NO, NO₂ and O₃ measured by the automatic stations, have been included in the study as well. Ambient air profiles of the different areas were studied, and the ozone formation dependent on VOCs and NO₂ levels was also analysed, taking into account the photochemical ozone creation potential (POCP) for different groups of VOCs.     

Correlation of the ratio of non-methane hydrocarbon and nitrogen oxide concentrations in the atmosphere and outdoor environment

A correlation between atmospheric pollution due to the emission of volatile organic compounds (VOC) and the non-methane hydrocarbon/nitrogen oxide (NMHC/NO_x) ratio has been determined. We supposed the source of NMHC in a region using the NMHC/NO_x ratio without needing to consider diffusion and dilution due to meteorological conditions. At general measurement stations in Neyagawa and Higashiosaka cities in Osaka Prefecture, the NMHC/NO_x ratio was high in summer though the NMHC and NO_x concentrations were high in early winter. Conversely, measurements of the ratio at a traffic measurement station in Shijonawate did not have this pattern. That is, NMHC emission increased with the temperature in Neyagawa and Higashiosaka. It was concluded the waste plastic processing facility increased the NMHC/NO_x ratio by comparing the change in the annually averaged NMHC/NO_x ratio at Neyagawa and Higashiosaka with the developments of disposal and treatment facilities in Neyagawa. In the case of Neyagawa, ventilation is not suitable for improving indoor air quality, because the outdoor pollution level can be higher than that indoors. The NMHC/NO_x ratio is a useful index to evaluate the change in the regional environment due to VOC pollution, and it can judge whether outdoor air can improve indoor air quality by ventilation.     

Micromap plots to visualize air pollution at national and local level in Korea

Air pollution is a persistent and pervasive environmental problem with health implications and economic costs for society. In this study, we introduce a new approach for visualizing air pollution data and describe how spatial patterns of air pollutants can be examined simultaneously using linked micromap plots. To explore the potential utility of the plots, we analysed and visualized Korean air pollution data for the period 1989–2012 at national and local level. Our analysis revealed that sulphur dioxide (SO₂), fine particle and carbon monoxide decreased for the period, but ozone increased uniquely. The pollution level of Jeju was lowest. Daegu and Gyeonggi showed the highest levels. Daegu had highest values in both range and interquartile range. SO₂ decreased the most in Gangwon which had formerly had the largest number of coal mines. Regions with high levels of fine particles were located mainly in the northwest, probably influenced by dust, and in the southeast, industrialized areas.     

Air monitoring network program in Saudi Arabia

The Kingdom of Saudi Arabia has initiated a program to install air quality network stations throughout the country in order to measure concentration of the ambient air pollutants. The site selection of these stations is an important objective to be accomplished and must be done based on scientific and rational work. To accomplish this objective, a modified version of atmospheric transport and dispersion model, known as air resources laboratories - atmospheric transport and dispersion (ARLATAD) model, is used to evaluate long range transport and diffusion of air pollutants from major pollution causing sources such as refineries, open-air burning of associated gases of oil fields and major industries.Hourly meteorological data for a period of three years (from 1977 to 1979) on wind speed, wind direction, pressure, and temperature from 20 synoptic stations in Saudi Arabia is processed and used as model input. In addition to these, meteorological data from three upper air stations is also processed in order to determine base and top of critical inversion heights.Various pollution causing sources are identified within the study area. Air trajectories are drawn with sources as the origins of the trajectories and the dispersion characteristics is studied with distance and time. Based on long term meteorological records, the adversely affected zones are statistically identified for potential station sites.     

Evaluation of a multiple regression model for the forecasting of the concentrations of NOx and PM10 in Athens and Helsinki

Forecasting models based on stepwise multiple linear regression (MLR) have been developed for Athens and Helsinki. The predictor variables were the hourly concentrations of pollutants (NO, NO₂, NO_x, CO, O₃, PM_2.5 and PM₁₀) and the meteorological variables (ambient temperature, wind speed/direction, and relative humidity) and in case of Helsinki also Monin-Obukhov length and mixing height of the present day. The variables to be forecasted are the maximum hourly concentrations of PM₁₀ and NO_x, and the daily average PM₁₀ concentrations of the next day. The meteorological pre-processing model MPP-FMI was used for computing the Monin-Obukhov length and the mixing height. The limitations of such statistical models include the persistence of both the meteorological and air quality situation; the model cannot account for rapid changes (on a temporal scale of hours or less than a day) that are commonly associated, e.g., with meteorological fronts, or episodes of a long-range transport origin. We have selected the input data for the model from one urban background and one urban traffic station both in Athens and Helsinki, in 2005. We have used various statistical evaluation parameters to analyze the performance of the models, and inter-compared the performance of the predictions for both cities. Forecasts from the MLR model were also compared to those from an Artificial Neural Network model (ANN) to investigate, if there are substantial gains that might justify the additional computational effort. The best predictor variables for both cities were the concentrations of NO_x and PM₁₀ during the evening hours as well as wind speed, and the Monin-Obukhov length. In Athens, the index of agreement (IA) for NO_x ranged from 0.77 to 0.84 and from 0.69 to 0.72, in the warm and cold periods of the year. In Helsinki, the corresponding values of IA ranged from 0.32 to 0.82 and from 0.67 to 0.86 for the warm and cold periods. In case of Helsinki the model accuracy was expectedly better on the average, when Monin-Obukhov length and mixing height were included as predictor variables. The models provide better forecasts of the daily average concentration, compared with the maximum hourly concentration for PM₁₀. The results derived by the ANN model where only slightly better than the ones derived by the MLR methodology. The results therefore suggest that the MLR methodology is a useful and fairly accurate tool for regulatory purposes.     

Intercomparison of air quality data using principal component analysis, and forecasting of PM₁₀ and PM₂.₅ concentrations using artificial neural networks, in Thessaloniki and Helsinki

In this paper we propose a methodology consisting of specific computational intelligence methods, i.e. principal component analysis and artificial neural networks, in order to inter-compare air quality and meteorological data, and to forecast the concentration levels for environmental parameters of interest (air pollutants). We demonstrate these methods to data monitored in the urban areas of Thessaloniki and Helsinki in Greece and Finland, respectively. For this purpose, we applied the principal component analysis method in order to inter-compare the patterns of air pollution in the two selected cities. Then, we proceeded with the development of air quality forecasting models for both studied areas. On this basis, we formulated and employed a novel hybrid scheme in the selection process of input variables for the forecasting models, involving a combination of linear regression and artificial neural networks (multi-layer perceptron) models. The latter ones were used for the forecasting of the daily mean concentrations of PM₁₀ and PM_2.5 for the next day. Results demonstrated an index of agreement between measured and modelled daily averaged PM₁₀ concentrations, between 0.80 and 0.85, while the kappa index for the forecasting of the daily averaged PM₁₀ concentrations reached 60% for both cities. Compared with previous corresponding studies, these statistical parameters indicate an improved performance of air quality parameters forecasting. It was also found that the performance of the models for the forecasting of the daily mean concentrations of PM₁₀ was not substantially different for both cities, despite the major differences of the two urban environments under consideration.     

Pollution from energy supply,conversion and use a review of the U.K. problem

Trends in U.K. consumption of coal, oil, natural gas, nuclear and hydroelectric energy are discussed, and forecasts of use to the year 2000 A.D. are given. More detailed forecasts of fuel use by different sectors to 1985 are presented. Wastes, the resulting pollution and their likely future trends from the following energy sources are reviewed: primary energy — oil treatment, natural gas transhipment, coal production and nuclear and hydroelectric power: secondary energy — electricity generation, coking and gas making: tertiary energy — use of fuels in transport and the domestic sector. Emission forecasts for several air pollutants from all energy sources to 1985 are presented, the pollution and damage arising being discussed. The need for further waste and pollutant monitoring is then debated, and the necessity of continuing to consider environmental protection in energy policy decisions, along with fuel conservation and relative price is stressed.     

Forecasting of daily air quality index in Delhi

As the impact of air pollutants on human health through ambient air address much attention in recent years, the air quality forecasting in terms of air pollution parameters becomes an important topic in environmental science. The Air Quality Index (AQI) can be estimated through a formula, based on comprehensive assessment of concentration of air pollutants, which can be used by government agencies to characterize the status of air quality at a given location. The present study aims to develop forecasting model for predicting daily AQI, which can be used as a basis of decision making processes. Firstly, the AQI has been estimated through a method used by US Environmental Protection Agency (USEPA) for different criteria pollutants as Respirable Suspended Particulate Matter (RSPM), Sulfur dioxide (SO₂), Nitrogen dioxide (NO₂) and Suspended Particulate Matter (SPM). However, the sub-index and breakpoint concentrations in the formula are made according to Indian National Ambient Air Quality Standard. Secondly, the daily AQI for each season is forecasted through three statistical models namely time series auto regressive integrated moving average (ARIMA) (model 1), principal component regression (PCR) (model 2) and combination of both (model 3) in Delhi. The performance of all three models are evaluated with the help of observed concentrations of pollutants, which reflects that model 3 agrees well with observed values, as compared to the values of model 1 and model 2. The same is supported by the statistical parameters also. The significance of meteorological parameters of model 3 has been assessed through principal component analysis (PCA), which indicates that daily rainfall, station level pressure, daily mean temperature, wind direction index are maximum explained in summer, monsoon, post-monsoon and winter respectively. Further, the variation of AQI during the weekends (holidays) and weekdays are found negligible. Therefore all the days of week are accounted same in the models.     

Indoor and outdoor PM2.5 and PM10 concentrations in the air during a dust storm

Asian dust storms (ADS) originating from the arid deserts of Mongolia and China are a well-known springtime meteorological phenomenon throughout East Asia. The ventilation systems in office utilize air from outside and therefore it is necessary to understand how these dust storms affect the concentrations of PM_2.5 and PM₁₀ in both the indoor and outdoor air. We measured dust storm pollution particles in an office building using a direct-reading instrument (PC-2 Quartz Crystal Microbalance, QCM) that measured particle size and concentration every 10 min for 1 h, three times a day. A three-fold increase in the concentrations of PM_2.5 and PM₁₀ in the indoor and outdoor air was recorded during the dust storms. After adjusting for other covariates, autoregression models indicated that PM_2.5 and PM₁₀ in the indoor air increased significantly (21.7 μg/m³ and 23.0 μg/m³ respectively) during dust storms. The ventilation systems in high-rise buildings utilize air from outside and therefore the indoor concentrations of fine and coarse particles in the air inside the buildings are significantly affected by outside air pollutants, especially during dust storms.     

Exposure to household air pollution from biomass‐burning cookstoves and HbA1c and diabetic status among Honduran women

Household air pollution from biomass cookstoves is estimated to be responsible for more than two and a half million premature deaths annually, primarily in low and middle‐income countries where cardiometabolic disorders, such as Type II Diabetes, are increasing. Growing evidence supports a link between ambient air pollution and diabetes, but evidence for household air pollution is limited. This cross‐sectional study of 142 women (72 with traditional stoves and 70 with cleaner‐burning Justa stoves) in rural Honduras evaluated the association of exposure to household air pollution (stove type, 24‐hour average kitchen and personal fine particulate matter [PM_2.5] mass and black carbon) with glycated hemoglobin (HbA1c) levels and diabetic status based on HbA1c levels. The prevalence ratio (PR) per interquartile range increase in pollution concentration indicated higher prevalence of prediabetes/diabetes (vs normal HbA1c) for all pollutant measures (eg, PR per 84 μg/m³ increase in personal PM_2.5, 1.49; 95% confidence interval [CI], 1.11‐2.01). Results for HbA1c as a continuous variable were generally in the hypothesized direction. These results provide some evidence linking household air pollution with the prevalence of prediabetes/diabetes, and, if confirmed, suggest that the global public health impact of household air pollution may be broader than currently estimated.     

An experimental study of air quality inside large athletic halls

Air quality in two large athletic halls with different ventilation (natural and mechanical) was investigated in relation to outdoor pollution and meteorological conditions. Simultaneous measurements of O₃, NO, NO₂ and SO₂ were performed in the halls at two heights (at the arena and spectators’ seats) and outdoors. BTX concentrations at the spectators’ seats and outdoor NMHCs, CH₄, PM₁₀ and CO concentrations were also measured. Analysis of diurnal variations of the pollutants’ concentrations, cross correlation analysis of the concentration time-series and principal component analysis were applied to the collected data. Results revealed that outdoor pollution significantly affected indoor air quality of both halls. However, this effect was different for the two buildings, depending on the ventilation types, the wind direction prevailing at the areas and the kind of indoor activity recorded. It was found that the latter parameters controlled the pollutants concentration levels in the halls and their response to the changes of the outdoor pollution levels. Temperature and pollution stratification enhancing during athletic events were also evident in both halls but with different characteristics observed, such as the spatial distribution of the indoor pollutants. The airflow patterns prevailing in each hall, imposed by the ventilation operation schemes were important factors.     

The contribution of activity-based transport models to air quality modelling: A validation of the ALBATROSS-AURORA model chain

The potential advantages of using activity-based transport models for air quality purposes have been recognized for a long time but models that have been developed along these lines are still scarce. In this paper we demonstrate that an activity-based model provides useful information for predicting hourly ambient pollutant concentrations. For this purpose, the traffic emissions obtained in a previous application of the activity-based model ALBATROSS were used as input for the AURORA air quality model to predict hourly concentrations of NO₂, PM₁₀ and O₃ in the Netherlands. Predicted concentrations were compared with measured concentrations at 37 monitoring stations from the Dutch air quality monitoring network. A statistical analysis was performed to evaluate model performance for different pollutants, locations and time periods. Results confirm that modelled and measured concentrations present the same geographical and temporal variation. The overall index of agreement for the prediction of hourly pollutant concentrations amounted to 0.64, 0.75 and 0.57 for NO₂, O₃ and PM₁₀ respectively. Concerning the predictions for NO2, a major traffic pollutant, a more thorough analysis revealed that the ALBATROSS-AURORA model chain yielded better predictions near traffic locations than near background stations. Further, the model performed better in urban areas, on weekdays and during the day, consistent with the emission results obtained in a previous study. The results in this paper demonstrate the ability of the activity-based model to predict the contribution of traffic sources to local air pollution with sufficient accuracy and confirms the usefulness of activity-based transport models for air quality purposes. The fact that the ALBATROSS-AURORA chain provides reliable pollutant concentrations on hourly basis for the whole Netherlands instead of using only daily averages near traffic stations is a plus for future exposure studies aiming at more realistic exposure analyses and health impact assessments.     

Air pollution episodes associated with East Asian winter monsoons

A dozen multi-day pollution episodes occur from October to February in Hanoi, Vietnam due to prolonged anticyclonic conditions established after the northeast monsoon surges (cold surges). These winter pollution episodes (WPEs) account for most of the 24-h PM₁₀ exceedances and the highest concentrations of gaseous pollutants in Hanoi. In this study, WPEs were investigated using continuous air quality monitoring data and information on upper-air soundings and air mass trajectories. The 24-h pollutant concentrations are lowest during cold surges; concurrently rise thereafter reaching the highest levels toward the middle of a monsoon cycle, then decline ahead of the next cold surge. Each monsoon cycle usually proceeds through a dry phase and a humid phase as Asiatic continental cold air arrives in Hanoi through inland China then via the East China Sea. WPEs are associated with nighttime radiation temperature inversions (NRTIs) in the dry phase and subsidence temperature inversions (STIs) in the humid phase. In NRTI periods, the rush hour pollution peak is more pronounced in the evening than in the morning and the pollution level is about two times higher at night than in daytime. In STI periods, broad morning and evening traffic peaks are observed and pollution is as high at night as in daytime. The close association between pollution and winter monsoon meteorology found in this study for the winter 2003-04 may serve as a basis for advance warning of WPEs and for forecasting the 24-h pollutant concentrations.     

Ambient air pollution and daily mortality in Anshan, China: a time-stratified case-crossover analysis

Few case-crossover studies were conducted in China to investigate the acute health effects of air pollution. We conducted a time-stratified case-crossover analysis to examine the association between air pollution and daily mortality in Anshan, a heavily-polluted industrial city in northeastern China. Daily mortality, air pollution, and weather data in 2004-2006 in Anshan were collected. Time-stratified case-crossover approach was used to estimate the effect of air pollutants (PM₁₀, SO₂, NO₂ and CO) on total and cardiopulmonary mortality. Controls were selected as matched days of the week in the same month. Potential effect modifiers, such as gender and age, were also examined. We found significant associations between air pollution and daily mortality from cardiovascular diseases in Anshan. A 10 μg/m³ elevation of 2-day moving average (lag 01) concentration in PM₁₀, SO₂, NO₂ and CO corresponded to 0.67% (95% CI: 0.29%, 1.04%), 0.38% (95% CI: −0.06%, 0.83%), 2.11% (95% CI: 0.22%, 4.00%) and 0.04% (95% CI: 0.01%, 0.07%) increase of cardiovascular mortality. The associations for total and respiratory mortality were generally positive but statistically insignificant. The air pollution health effects were significantly modified by age, but not by gender. Conclusively, our study showed that short-term exposure to air pollution was associated with increased cardiovascular mortality in Anshan. These findings may have implications for local environmental and social policies.     

Modeling residential indoor concentrations of PM2.5, NO2, NOx,and secondhand smoke in the Subpopulations and Intermediate Outcome Measures in COPD (SPIROMICS) Air study

Increased outdoor concentrations of fine particulate matter (PM_2.5) and oxides of nitrogen (NO₂, NO_x) are associated with respiratory and cardiovascular morbidity in adults and children. However, people spend most of their time indoors and this is particularly true for individuals with chronic obstructive pulmonary disease (COPD). Both outdoor and indoor air pollution may accelerate lung function loss in individuals with COPD, but it is not feasible to measure indoor pollutant concentrations in all participants in large cohort studies. We aimed to understand indoor exposures in a cohort of adults (SPIROMICS Air, the SubPopulations and Intermediate Outcome Measures in COPD Study of Air pollution). We developed models for the entire cohort based on monitoring in a subset of homes, to predict mean 2-week–measured concentrations of PM_2.5, NO₂, NO_x, and nicotine, using home and behavioral questionnaire responses available in the full cohort. Models incorporating socioeconomic, meteorological, behavioral, and residential information together explained about 60% of the variation in indoor concentration of each pollutant. Cross-validated R² for best indoor prediction models ranged from 0.43 (NO_x) to 0.51 (NO₂). Models based on questionnaire responses and estimated outdoor concentrations successfully explained most variation in indoor PM_2.5, NO₂, NO_x, and nicotine concentrations.     

Long-range forecasting of regional manpower requirements: The state of Illinois in 1980

This paper presents alternate detailed forecasts of occupational requirements for the state of Illinois in 1980. These manpower forecasts, developed on the basis of different national economic policies and Federal budget priorities, are compared with the 1980 Illinois employment projections estimated by the State manpower planning agency and the differences in methodology are analyzed. Sources of possible error in the official State forecasts are indicated and a potentially more accurate picture of Illinois 1980 manpower requirements is developed. It is discussed how the model utilized here could be adapted to other States and regions.This research was conducted while he was on the faculty of the University of Illinois at Urbana-Champaign. He is indebted to Janet Spoonamore and Walter Nidzieko for the programming work involved here and to Firoze Gandhi for research assistance. The opinions expressed here as well as any errors remain the sole responsibility of the author. This work was supported in part by the Center for Advanced Computation of the University of Illinois.     

Reflectance spectroscopy is an effective tool for monitoring soot pollution in an urban suburb

This study examines whether converting the fossil fuel of the Tel Aviv power station from oil to gas influences air pollution in the local urban environment. To this end, the spectral properties of accumulated dust on tree leaves and paper bags were assessed before (2004) and after (2006) the conversion. The sampling site was a garden in a neighborhood located 2700 m downwind of the power station. In addition, air pollution concentrations and particulate matter parameters recorded by a local meteorological station were analyzed (PM₁₀, NO_x, NO₂, NO, and SO₂). Although differences in the average monthly concentration of pollution parameters are mostly insignificant between the two periods, the accumulated particulate matter exhibits considerably different spectral patterns. All first period samples exhibit a distinctly concave slope in the spectral region between 400 and 1400 nm, indicative of high amounts of soot, most likely due to the combustion products of fuel oil exhausted by the power plant. In contrast, the second period samples exhibit spectra that indicate reduced soot content and even appear slightly convex, evidencing the presence of dust of mineral origin, a feature likely masked by the soot in the first period. Thus, the spectral data support that the power plant conversion results in less pollution. More generally, this study corroborates that VIS-NIR-SWIR spectroscopy characterizes key properties of the particulate layer accumulating on sampled surfaces and thus, is a powerful method for monitoring the urban environment.