Trends in air quality and population exposure in Santiago, Chile, 1989–2001

This study focused on establishing trends in the period 1988–2001 in PM_2.5, PM₁₀ and ozone concentrations in Santiago, Chile, and linking those to population exposure. There is strong seasonality in the concentration levels, driven by prevailing meteorological conditions, with the concentration of particulates peaking at the beginning of winter, whereas the ozone concentration is highest during the summer. The levels of PM_2.5 and PM₁₀ have substantially decreased since the late 1980s and so has the population exposure. Nevertheless, the majority of the population is still exposed to annual average levels that are above standard values. The situation with ozone exposure is different; no substantial decrease can be observed in the data. If anything, certain parts of Santiago, notably the south-east, have shown increased levels of ozone. Overall population exposure indicates that the average person was more at risk of ozone in the year 2000 than they were in 1993.     

Air quality at Santiago,Chile: a box modeling approach II. PM2.5, coarse and PM10 particulate matter fractions

Ambient monitored data at Santiago, Chile, are analyzed using box models with the goal of assessing contributions of different economic activities to air pollution levels. The box modeling approach was applied to PM₁₀, PM_2.5 and coarse (PM₁₀–PM_2.5) particulate matter (PM) fractions; the period analyzed is 1989–1999. A linear model for each PM fraction was obtained, having as independent variables CO and SO₂ concentrations, plus a term proportional to (wind speed)⁻¹ that lumps together non-combustion emissions and secondary generation terms; wet scavenging is included as another independent variable. Model identification results show good agreement for the different parameters across monitoring stations. The washout ratios and scavenging coefficients agree with data published in the literature, being higher for the coarse PM fraction. The CO and SO₂ coefficients fitted for 1989–1995 agree with a priori estimates for the same period. Background estimates for the PM fractions are in agreement with measurement campaigns in upwind sites. Results show that transportation sources have become the dominant contributors to ambient PM levels, while stationary sources have decreased their contributions in the last years. The relative importance of mobile sources to PM_2.5 ambient concentrations has doubled in the last 10 years, whereas stationary sources have reduced their relative contributions to half the value in the early 1990s. Model estimates of regional background of PM_2.5 and PM₁₀ have decreased 50% and 22% in the last decade, respectively; coarse background has shown no significant change. The final conclusion is that there is room and need for a more intensive emission reduction strategy for Santiago, focusing on mobile sources. The approach pursued in this work is feasible for cities or regions where comprehensive, transport and chemistry models are not available yet, but estimates of air quality contributions are needed for policy purposes. The methodology requires data on ambient air quality measurements and surface meteorology.     

Estimations of primary and secondary organic carbon formation in PM2.5 aerosols of Santiago City,Chile

High concentration of fine airborne particulates is considered one of the major environmental pollutants in Santiago, the Chilean Capital city, which in 1997 was declared a PM₁₀ saturated zone. To date there is no control of the amounts of fine and coarse aerosols concentrations and the source and chemical characterizations of the PM_2.5 particulates in the carbonaceous fractions are not well known even though this fraction could be represented almost the 50% in mass of the PM_2.5.In this work, we present for the first time determinations of primary organic aerosol (POA) and secondary organic aerosol composition (SOA) fractions of the total mass of PM_2.5 particulates collected in the urban atmosphere of Santiago City. Our purpose is to know the anthropogenic contributions to the formation of SOA. To accomplish this we used the elemental carbon (EC) and organic carbon (OC) determinations developed by automatic monitoring stations installed in the city during the period 2002–2005, with a particular analysis of the summer time occurred in February 2004. Based on the EC tracer method, we have estimated the POA and SOA fraction and our data permit us to estimate the SOA reaching up to 20% of total organic aerosol matter, in good agreement to other measurements observed in large cities of Europe and U.S.A.     

Particulate matter in California: part 2--Spatial, temporal, and compositional patterns of PM2.5, PM10-2.5, and PM10

Geographic and temporal variations in the concentration and composition of particulate matter (PM) provide important insights into particle sources, atmospheric processes that influence particle formation, and PM management strategies. In the nonurban areas of California, annual-average PM2.5 and PM10 concentrations range from 3 to 10 microg/m3 and from 5 to 18 microg/m3, respectively. In the urban areas of California, annual-averages for PM2.5 range from 7 to 30 microg/m3, with observed 24-hr peaks reaching levels as high as 160 microg/m3. Within each air basin, exceedances are a mixture of isolated events as well as periods of elevated PM2.5 concentrations that are more prolonged and regional in nature. PM2.5 concentrations are generally highest during the winter months. The exception is the South Coast Air Basin, where fairly high values occur throughout the year. Annual-average PM2.5 mass, as well as the concentrations of major components, declined from 1988 to 2000. The declines are especially pronounced for the sulfate (SO4(2-)) and nitrate (NO3-) components of PM2.5 and PM10) and correlate with reductions in ambient levels of oxides of sulfur (SOx) and oxides of nitrogen (NOx). Annual averages for PM10-2.5 and PM10 exhibited similar downwind trends from 1994 to 1999, with a slightly less pronounced decrease in the coarse fraction.     

Prediction of maximum of 24-h average of PM10 concentrations 30 h in advance in Santiago,Chile

We have developed a neural network based model that uses values of PM10 concentrations measured until 6 p.m. on the present day plus measured and forecasted values of meteorological variables as input in order to predict the level reached by the maximum of the 24-h moving average (24MA) of PM10 concentration on the next day. We have adjusted the parameters of the model using 1998 data to predict 1999 conditions and 1999 data to forecast 2000 maximum concentrations. We have found that among the relevant meteorological input variables, the forecasted difference between maximum and minimum temperature is the most important. Due to the fact that local authorities impose restrictions to emissions on days when the maximum of 24MA of PM10 concentration is expected to exceed 240 μg/m³, we have corrected the measured concentrations on these days before evaluating the efficacy of the forecasting model. Percent errors in forecasting the numerical value are of the order of 20%. The performance of the neural network is better than that of a linear model with the same inputs, but the difference being not great is an indication that the right choice of input variables may be more important than the decision to use a linear or a nonlinear model.     

Particulate matter in California: part 1--Intercomparison of several PM2.5, PM10-2.5, and PM10 monitoring networks

It will be many years before the recently deployed network of fine particulate matter with an aerodynamic diameter less than 2.5 microm (PM2.5) Federal Reference Method (FRM) samplers produces information on nonattainment areas, trends, and source impacts. However, data on PM2.5 and its major constituents have been routinely collected in California for the past 20 years. The California Air Resources Board operated as many as 20 dichotomous (dichot) samplers for PM2.5 and coarse PM (PM10-2.5). The California Acid Deposition Monitoring Program (CADMP) collected 12-h-average PM2.5 and PM10 from 1988 to 1995 at ten urban and rural sites and 24-h-average PM2.5 at five urban sites since 1995. Beginning in 1994, the Children's Health Study collected 2-week averages of PM2.5 in 12 communities in southern California using the Two-Week Sampler (TWS). Comparisons of collocated samples establish relationships between the dichot, CADMP, and TWS samplers and the 82-site network of PM2.5 FRM samplers deployed since 1999 in California. PM mass data from the different monitoring programs have modest to high correlation to FRM mass data, fairly small systematic biases and negative proportional biases ranging from 7 to 22%. If the biases are taken into account, all of the programs should be considered comparable with the FRM program. Thus, historical data can be used to develop long-term PM trends in California.     

Use of the light absorption coefficient to monitor elemental carbon and PM2.5--example of Santiago de Chile

The optical absorption coefficient, particulate matter with an aerodynamic diameter <2.5 microm, and elemental carbon (EC) have been measured simultaneously during winter and spring of 2000 in the western part of Santiago, Chile (Pudahuel district). The optical measurements were carried out with a low-cost instrument recently developed at the University of Santiago. From the data, a site-specific mass absorption coefficient of 4.45+/-0.01 m2/g has been found for EC. In addition, a mass absorption coefficient of 1.02+/-0.03 m2/g has been obtained for PM2.5. These coefficients can be used during the colder months (May-August) to obtain EC concentration or PM2.5 from a measurement of the light absorption coefficient (sigmaa). The high correlation that has been found between these variables indicates that sigmaa is a good indicator of the degree of contamination of urbanized areas. The data also show an increase in PM2.5 and EC concentration during winter and an increase in the ratio of EC to PM2.5. When the EC/PM2.5 ratio is calculated during rush hour (7:00 a.m.-11:00 a.m.) and during part of the night (9:00 p.m.-2:00 a.m.), it is found that the increase is caused by higher concentration levels of EC at night. These results suggest that the rise in the EC concentration is caused by emissions from heating and air mass transport of pollution from other parts of the city, while traffic contribution remains approximately constant.     

PM10 and PM2.5 concentrations in Central and Eastern Europe:: results from the Cesar study

Between November 1995 and October 1996, particulate matter concentrations (PM₁₀ and PM_2.5) were measured in 25 study areas in six Central and Eastern European countries: Bulgaria, Czech Republic, Hungary, Poland, Romania and Slovak Republic. To assess annual mean concentration levels, 24-h averaged concentrations were measured every sixth day on a fixed urban background site using Harvard impactors with a 2.5 and 10 μm cut-point. The concentration of the coarse fraction of PM₁₀ (PM_10−2.5) was calculated as the difference between the PM₁₀ and the PM_2.5 concentration. Spatial variation within study areas was assessed by additional sampling on one or two urban background sites within each study area for two periods of 1 month. QA/QC procedures were implemented to ensure comparability of results between study areas. A two to threefold concentration range was found between study areas, ranging from an annual mean of 41 to 98 μg m⁻³ for PM₁₀, from 29 to 68 μg m⁻³ for PM_2.5 and from 12 to 40 μg m⁻³ for PM_10−2.5. The lowest concentrations were found in the Slovak Republic, the highest concentrations in Bulgaria and Poland. The variation in PM₁₀ and PM_2.5 concentrations between study areas was about 4 times greater than the spatial variation within study areas suggesting that measurements at a single sampling site sufficiently characterise the exposure of the population in the study areas. PM₁₀ concentrations increased considerably during the heating season, ranging from an average increase of 18 μg m⁻³ in the Slovak Republic to 45 μg m⁻³ in Poland. The increase of PM₁₀ was mainly driven by increases in PM_2.5; PM_10−2.5 concentrations changed only marginally or even decreased. Overall, the results indicate high levels of particulate air pollution in Central and Eastern Europe with large changes between seasons, likely caused by local heating.     

Analysis of PM2.5and PM10 in the Atmosphere of Mexico City during 2000-2002

Abstract

During the last 10 years, high atmospheric concentrations of airborne particles recorded in the Mexico City metropolitan area have caused concern because of their potential harmful effects on human health. Four monitoring campaigns have been carried out in the Mexico City metropolitan area during 2000-2002 at three sites: (1) Xalos-toc, located in an industrial region; (2) La Merced, located in a commercial area; and (3) Pedregal, located in a residential area. Results of gravimetric and chemical analyses of 330 samples of particulate matter (PM) with an aerodynamic diameter less than 2.5 μm (PM_2.5) and PM with an aerodynamic diameter less than 10 μm (PM₁₀) indicate that (1) PM_2.5/PM₁₀ average ratios were 0.42, 0.46, and 0.52 for Xalostoc, La Merced, and Pedregal, respectively; (2) the highest PM_2.5 and PM₁₀ concentrations were found at the industrial site; (3) PM_2.5 and PM₁₀ concentrations were lower at nighttime; (4) PM_2.5 and PM₁₀ spatial averages concentrations were 35 and 76 μg/m³, respectively; and (5) when the PM_2.5 standard was exceeded, nitrate, sulfate, ammonium, organic carbon, and elemental carbon concentrations were high. Twenty-four hour averaged PM_2.5 concentrations in Mexico City and Sao Paulo were similar to those recorded in the 1980s in Los Angeles. PM₁₀ concentrations were comparable in Sao Paulo and Mexico City but 3-fold lower than those found in Santiago.     

Analysis of PM2.5 and PM10 in the atmosphere of Mexico City during 2000-2002

During the last 10 years, high atmospheric concentrations of airborne particles recorded in the Mexico City metropolitan area have caused concern because of their potential harmful effects on human health. Four monitoring campaigns have been carried out in the Mexico City metropolitan area during 2000-2002 at three sites: (1) Xalostoc, located in an industrial region; (2) La Merced, located in a commercial area; and (3) Pedregal, located in a residential area. Results of gravimetric and chemical analyses of 330 samples of particulate matter (PM) with an aerodynamic diameter less than 2.5 microm (PM2.5) and PM with an aerodynamic diameter less than 10 microm (PM10) indicate that (1) PM2.5/PM10 average ratios were 0.42, 0.46, and 0.52 for Xalostoc, La Merced, and Pedregal, respectively; (2) the highest PM2.5 and PM10 concentrations were found at the industrial site; (3) PM2.5 and PM10 concentrations were lower at nighttime; (4) PM2.5 and PM10 spatial averages concentrations were 35 and 76 microg/m3, respectively; and (5) when the PM2.5 standard was exceeded, nitrate, sulfate, ammonium, organic carbon, and elemental carbon concentrations were high. Twenty-four hour averaged PM2.5 concentrations in Mexico City and Sao Paulo were similar to those recorded in the 1980s in Los Angeles. PM10 concentrations were comparable in Sao Paulo and Mexico City but 3-fold lower than those found in Santiago.     

Statistical characterization of atmospheric PM10 and PM2.5 concentrations at a non-impacted suburban site of Istanbul, Turkey

Inhalable particulate matter (PM10) has been monitored at several stations by Istanbul Municipality. On the other hand, information about fine fraction aerosols (PM2.5) in Istanbul atmosphere was not reported. In this study, 86 daily aerosol samples were collected between July 2002 and July 2003. The PM10 annual arithmetic mean value of 47.1 microg m(-3), was lower than the Turkish air quality standard of 60 microg m(-3). On the other hand, this value was found higher than the annual European Union air quality PM(10) standard of 40 microg m(-3). Furthermore, the annual mean concentration of PM2.5 20.8 microg m(-3) was found higher than The United States EPA standard of 15 microg m(-3). The statistics and relationships of fine, coarse, and inhalable particles were studied. Cyclic behavior of the monthly average concentrations of PM10 and PM2.5 data were investigated. Several frequency distribution functions were used to fit the measured data. According to Chi-squared and Kolmogorov-Smirnov tests, the frequency distributions of PM2.5 and PM10 data were found to fit Log-logistic functions.     

Prediction of NO and NO2 concentrations near a street with heavy traffic in Santiago,Chile

Based on NO concentrations and meteorological variables recorded hourly at a point close to an avenue with heavy traffic in the city of Santiago, we are able to build a simple model that allows prediction of NO concentrations several hours in advance. Predicted NO concentrations in conjunction with forecasted meteorological data may be used to predict NO₂ concentrations with reasonable accuracy. We compare predictions generated using persistence, linear regressions and multi layer neural networks.     

Spatial and temporal characterization of PM2.5 mass concentrations in California, 1980-2007

Systematic measurement of fine particulate matter (aerodynamic diameter less than 2.5 microm [PM2.5]) mass concentrations began nationally with implementation of the Federal Reference Method (FRM) network in 1998 and 1999. In California, additional monitoring of fine particulate matter (PM) occurred via a dichotomous sampler network and several special studies carried out between 1982 and 2002. The authors evaluate the comparability of FRM and non-FRM measurements of PM2.5 mass concentrations and establish conversion factors to standardize fine mass measurements from different methods to FRM-equivalent concentrations. The authors also identify measurements of PM2.5 mass concentrations that do not agree with FRM or other independent PM2.5 mass measurements. The authors show that PM2.5 mass can be reconstructed to a high degree of accuracy (r2 > 0.9; mean absolute error approximately 2 microg m(-3)) from PM with an aerodynamic diameter < or =10 microm (PM10) mass and species concentrations when site-specific and season-specific conversion factors are used and a statewide record of fine PM mass concentrations by combining the FRM PM2.5 measurements, non-FRM PM2.5 measurements, and reconstructions of PM2.5 mass concentrations. Trends and spatial variations are evaluated using the integrated data. The rates of change of annual fine PM mass were negative (downward trends) at all 22 urban and 6 nonurban (Interagency Monitoring of Protected Visual Environments [IMPROVE]) monitoring locations having at least 15 yr of data during the period 1980-2007. The trends at the IMPROVE sites ranged from -0.05 to -0.25 microg m(-3) yr(-1) (median -0.11 microg m(-3) yr(-1)), whereas urban-site trends ranged from -0.13 to -1.29 microg m(-3) yr(-1) (median -0.59 microg m(-3) yr(-1)). The urban concentrations declined by a factor of 2 over the period of record, and these decreases were qualitatively consistent with changes in emissions of primary PM2.5 and gas-phase precursors of secondary PM. Mean PM2.5 mass concentrations ranged from 3.3 to 7.4 microg m(-3) at IMPROVE sites and from 9.3 to 37.1 microg m(-3) at urban sites.     

PM10, PM2.5 and PM1.0—Emissions from industrial plants—Results from measurement programmes in Germany

Emission measurement programmes were carried out at industrial plants in several regions of Germany to determine the fine dust in the waste gases; the PM₁₀, PM_2.5 and PM_1.0 fractions were sampled using a cascade impactor technique. The installations tested included plants used for: combustion (brown coal, heavy fuel oil, wood), cement production, glass production, asphalt mixing, and processing plants for natural stones and sand, ceramics, metallurgy, chemical production, spray painting, wood processing/chip drying, poultry farming and waste treatment. In addition waste gas samples were taken from small-scale combustion units, like domestic stoves, firing lignite briquettes or wood.In total 303 individual measurement results were obtained during 106 different measurement campaigns. In the study it was found that in more than 70% of the individual emission measurement results from industrial plants and domestic stoves the PM₁₀ portion amounted to more than 90% and the PM_2.5 portion between 50% and 90% of the total PM (particulate matter) emission. For thermal industrial processes the PM_1.0 portion constituted between 20% and 60% of the total PM emission.Typical particle size distributions for different processes were presented as cumulative frequency distributions and as frequency distributions. The particle size distributions determined for the different plant types show interesting similarities and differences depending on whether the processes are thermal, mechanical, chemical or mixed. Consequently, for the groups of plant investigated, a major finding of this study has been that the particle size distribution is a characteristic of the industrial process. Attempts to correlate particle size distributions of different plants to different gas cleaning technologies did not lead to usable results.     

2015年南京市PM2.5与PM10的污染特征

分析了2015年南京市PM2.5和PM10的浓度特征和大致来源类型。PM2.5和PM10的年均浓度分别为56.6 μg·m-3和96.5 μg·m-3,污染水平较高。颗粒物浓度的季节变化特征一致：冬 > 春 > 秋 > 夏;PM2.5的日变化呈"单峰单谷"型,而PM10的呈"单峰双谷"型。颗粒物浓度在城区高于郊区;植被茂盛区域的浓度较低。对PM2.5/PM10而言,比值在冬季和梅雨期较大,分别受取暖和降水的影响;比值在春季和夏末秋初较小,分别受沙尘和秸秆焚烧的影响。PM2.5多为二次颗粒物,PM10多为一次颗粒物;固定污染源对PM2.5的间接贡献和对PM10的直接贡献较移动污染源而言更大。     

Chemical speciation of PM2.5 and PM10 in south Phoenix, AZ, USA

Phoenix, AZ, experiences high particulate matter (PM) episodes, especially in the wintertime. The spatial variation of the PM concentrations and resulting differences in exposure is of particular concern. In this study, PM2.s (PM with aerodynamic diameter <2.5 microm) and PM10 (PM with aerodynamic diameter <10 microm) samples were collected simultaneously from the east and west sides of South Phoenix and at a control site in Tempe and analyzed for trace elements and bulk elemental and organic carbon. Measurements showed that although PM2.5 concentrations had similar trends in temporal scale across all sites, concentrations of PM10 did not. The difference in PM10 concentrations and fluctuation across the three sites suggest effects of a local soil source as evidenced by high concentrations of Al, Ca, and Fe in PM10. K and anthropogenic elements (e.g., Cu, Pb, and Zn) in PM2.5 samples on January 1 were strikingly high, suggesting the influence of New Year's fireworks. Concentrations of toxic elements (e.g., Pb) in the study presented here are not different from similar studies in other U.S. cities. Application of principal component analysis indicated two broad categories of emission sources--soil and combustion--together accounting for 80 and 90% of variance, respectively, in PM2.5 and PM10. The soil and combustion components explained approximately 60 and 30% of the variance in PM10, respectively, whereas combustion sources dominated PM2.5 (>50% variance). Many elements associated with anthropogenic sources were highly enriched, with enrichment factors in PM2.5 an order of magnitude higher than in PM10 relative to surface soil composition in the study area.     

Prediction of sulfur dioxide concentrations at a site near downtown Santiago,Chile

We have analyzed the possibility to predict hourly averages of sulfur dioxide concentrations in the atmosphere at a site not far from the downtown area in the city of Santiago, Chile. We have compared the forecasts produced assuming persistence, linear regressions and feed forward neural networks. The effect of meteorological conditions is included by using forecasted values of temperature, relative humidity and wind speed at the time of the intended prediction as inputs to the different models. The best predictions for hourly averages are obtained with a three-layer neural network that has hourly averages of sulfur dioxide concentrations every 6 h on the previous day plus the actual values of the meteorological variables as input. Training the network with 1995 data, error in 8 h in advance prediction for 1996 data is of the order of 30%.     

Use of the aerodynamic particle sizer to measure ambient PM10-2.5: the coarse fraction of PM10

The Aerodynamic Particle Sizer (APS 3321, TSI, Inc., Shoreview, MN) rapidly measures particle number concentration by size from 0.5 to 20 microm. This work used simple assumptions for particle shape factor and density to estimate ambient coarse mode particulate matter, PM10-2.5, from APS number concentration data. This estimate was compared with that measured with time-integrated, filter-based federal reference method (FRM) samplers in four U.S. field studies: two in Phoenix, AZ; one in Gary, IN; and one in Riverside, CA. Near one-to-one agreement and a strong linear relationship were observed between APS-estimated and FRM-measured PM10-2.5 in the first Phoenix, AZ study (slope = 0.90, R2 = 1.00); the second Phoenix, AZ study (slope = 0.99, R2 = 0.99); and the Riverside, CA study (slope = 1.00, R2 = 0.84). In the Gary, IN study, PM10-2.5 estimates made with data from the APS tended to be less than that measured with the FRM samplers (slope = 0.57), but the linear relationship between the two methods was still strong (R2 = 0.90). Particle-bound water associated with wet atmospheric conditions may account for these differences. Additional testing is required to resolve this issue.     

Wintertime PM2.5 and PM10 Source Apportionment at Sacramento,California

ABSTRACT

The chemical mass balance (CMB) model was applied to winter (November through January) 1991–1996 PM2.5 and PM10 data from the Sacramento 13th and T Streets site in order to identify the contributions from major source categories to peak 24-hr ambient PM_2.5 and PM₁₀ levels. The average monthly PM₁₀ monitoring data for the nine-year period in Sacramento County indicate that elevated concentrations are typical in the winter months. Concentrations on days of highest PM₁₀ are dominated by the PM2.5 fraction. One factor contributing to increased PM_2.5 concentrations in the winter is meteorology (cool temperatures, low wind speeds, low inversion layers, and more humid conditions) that favors the formation of secondary nitrate and sulfate aerosols. Residential wood burning also elevates fine particulate concentrations in the Sacramento area.

The results of the CMB analysis highlight three key points. First, the source apportionment results indicate that primary motor vehicle exhaust and wood smoke are significant sources of both PM_2.5 and PM₁₀ in winter. Second, nitrates, secondarily formed as a result of motor-vehicle and other sources of nitrogen oxide (NO_x), are another principal cause of the high PM_2.5 and PM₁₀ levels during the winter months. Third, fugitive dust, whether it is resuspended soil and dust or agricultural tillage, is not the major contributor to peak winter PM_2.5 and PM10 levels in the Sacramento area.