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1.
Air quality has been deteriorated seriously in urban areas as a result of increasing anthropogenic activities. Meteorological conditions affect air pollution levels in the urban atmosphere significantly due to their important role in transport and dilution of the pollutants. This paper aims to investigate usability of some promising statistical methods for examining the impacts of metrological factors on SO2 and PM10 levels. Data were collected from city centre of Kocaeli in winter periods from 2007 to 2010 as pollutant concentrations increase in winters due to expanding combustion facilities. Results of bivariate correlation analysis showed that humidity and rainfall have remarkable negative correlations with the pollutants. Multiple linear regression models and artificial neural network (ANN) models were used to predict next day's PM10 and SO2 levels. In regression models calculated R2 values were 0.89 and 0.75 for PM10 and SO2, respectively. Among the various architectures, single layer networks provided better performance in ANN applications. Highest R2 values were obtained as 0.89 and 0.69 for PM10 and SO2, respectively, by using appropriate networks.  相似文献   

2.
In this study, it was aimed to characterize temporal variations of air pollutants for determining contribution to pollution episodes and to obtain correlations between these pollutants. With this aim we used data analysis for measured sulfur dioxide (SO2), particulate matter (PM, black fume and PM10), nitrogen oxides (NOx), ozone (O3), carbon monoxide (CO), methane (CH4), and non‐methane hydrocarbons (NMHC) recorded in Kocaeli, one of the most industrilizated cities of Turkey. Pollutant concentrations were the results of continuous and semi‐automatic measurements. Semi‐automatic measurements of SO2 and PM (black fume) were enclosing period from 1987 to 2008 whereas continuous monitoring of all pollutants included years of 2007–2009. In the first stage of the study daily, monthly, annual, and seasonal variations of pollution were researched. Annual average concentrations were compared with limits set by Air Quality Protection Regulation (AQPR), Air Quality Evaluation and Management Regulation (AQEMR), World Health Organization (WHO), European Union (EU), and National Ambient Air Quality Standards (USEPA). In the following stage relationships between pollutants such as NO2–O3, NOx–CO, NOx–NMHC, and NOx–SO2 were investigated and correlation coefficients were determined as 0.87, 0.56, 0.51, and 0.69, respectively. R2 values of regression models developed from these correlations were 0.78, 0.56, 0.34, and 0.72, respectively. Vehicle density of the traffic was evaluated with NOx–O3 emissions and decrease was seen in NOx emissions due to decreasing vehicle density at weekends whereas O3 concentrations increased. These correlations enable prediction of the parameters that cannot be measured which is important for providing improvement in early warning systems.  相似文献   

3.
Despite the existing public and government measures for monitoring and control of air quality in Bulgaria, in many regions, including typical and most numerous small towns, air quality is not satisfactory. In this paper, factor analysis and Box–Jenkins methodology are applied to examine concentrations of primary air pollutants such as NO, NO2, NOx, PM10, SO2 and ground level O3 in the town of Blagoevgrad, Bulgaria within a 1 year period from 1st September 2011 to 31st August 2012, based on hourly measurements. By using factor analysis with PCA and Promax rotation, a high multicollinearity between the six pollutants has been detected. The pollutants were grouped in three factors and the degree of contribution of the factors to the overall pollution was determined. This was interpreted as the presence of common sources of pollution. The main part of the study involves the performance of time series analysis and the development of univariate stochastic seasonal autoregressive integrated moving average (ARIMA) models with recording on a hourly basis as seasonality. The study also incorporates the Yeo–Johnson power transformation for variance stabilizing of the data and model selection by using Bayersian information criterion. The obtained SARIMA models demonstrated very good fitting performance with regard to the observed air pollutants and short-term predictions for 72 h ahead, in particular in the case of ozone and particulate matter PM10. The presented statistical approaches allow the building of non-complex models, effective for short-term air pollution forecasting and useful for advance warning purposes in urban areas.  相似文献   

4.
Atmospheric particulate matter (PM) is one of the pollutants that may have a significant impact on human health. Data collected over 7 years from the air quality monitoring station at the LD-III steelworks, belonging to the Arcelor-Mittal Steel Company, located in the metropolitan area of Avilés (Principality of Asturias, Northern Spain), is analyzed using four different mathematical models: vector autoregressive moving-average, autoregressive integrated moving-average (ARIMA), multilayer perceptron neural networks and support vector machines with regression. Measured monthly, the average concentration of pollutants (SO2, NO and NO2) and PM10 (particles with a diameter less than ?10 μm) is used as input to forecast the monthly average concentration of PM10 from one to 7 months ahead. Simulations showed that the ARIMA model performs better than the other models when forecasting 1 month ahead, while in the forecast from one to 9 months ahead the best performance is given by the support vector regression.  相似文献   

5.
The accuracy of atmospheric numerical model is important for the prediction of urban air pollution. This study investigated and quantified the uncertainties of meteorological and air quality model during multi-levels air pollution periods. We simulated the air quality of megacity Shanghai, China with WRF/CMAQ (Weather Research and Forecasting model and Community Multiscale Air Quality model) at both non-pollution and heavy-pollution episodes in 2012. The weather prediction model failed to reproduce the surface temperature and wind speed in condition of high aerosol loading. The accuracy of the air quality model showed a clear dropping tendency from good air quality conditions to heavily polluted episodes. The absolute model bias increased significantly from light air pollution to heavy air pollution for SO2 (from 2 to 14%) and for PM10 (from 1 to 33%) in both urban and suburban sites, for CO in urban sites (from 8 to 48%) and for NO2 in suburban sites (from 1 to 58%). A test of applying the Urban Canopy Model scheme to the WRF model showed fairly good improvement on predicting the meteorology field, but less significant effect on the air pollutants (6% for SO2 and 19% for NO2 decease in model bias found only in urban sites). This study gave clear evidence to the sensitivities of the model performance on the air pollution levels. It is suggested to consider this impact as a source for model bias in the model assessment and make improvement in the model development in the future.  相似文献   

6.
In this paper, a technique is proposed in order to study triple time series. It combines the variable of interest, sulfur dioxide (SO2) with two related meteorological variables. Hence, three variables measured at the same time points are jointly analyzed. Instead of using classical multiple time series analysis, it is suggested to consider the measurements of the two meteorological variables as coordinates of a two-dimensional space and the simultaneous observation of the third variable (associated SO2 concentrations) at each pair of coordinates. Subsequently, well-known optimum interpolation is used for predicting the SO2 concentrations on the basis of six meteorological variables. All the variables of the study are measured at the same times (all days in 2000) around the city of Istanbul, Turkey. The triple diagrams, in the form of contour maps, help to answer various questions concerning the SO2 concentration variability with respect to meteorological variables. The same diagrams also provide a basis for the prediction of SO2 concentrations. It is shown that the relative prediction error is less than 10%, which is acceptable for the practical studies.  相似文献   

7.
Abstract

An integrated model for the simulation and prediction of both snowmelt quantity and quality from seasonal snow cover in a mountain basin has been developed at the Institute of Hydrology and Hydraulics SAS in cooperation with the Geological Institute of Dionyz ?tur. The model will be used for both the simulation and forecast of snow accumulation and the accumulation of SO2- 4 washout. At the present time it is mostly used for simulation of the SO2- 4 concentration and water supply in snow. In this paper the results of SO2- 4 modelling in a brook are also presented.  相似文献   

8.
Most sulphur diagenesis models predict that SO42- concentrations decrease exponentially with increasing sediment depth and are lower than that of the overlying water throughout the sediments. Low SO42- concentrations (less than 0.2 mM) are common in the sediments of Lake Anna that receive acid mine drainage; however, sediment with as much as 20 mM SO42- at about 20cm below the sediment surface is also seen in this section of the lake. A decision tree was proposed to investigate the cause of the high SO42- concentrations at depth (HSD) in the sediment. The first possibility proposed was that an increase in the quantity of groundwater flowing through Lake Anna sediments may increase groundwater advection of SO42- or oxygen which would induce sulphide oxidation. This hypothesis was tested by measuring groundwater flow. HSD profiles were found in a discrete region of the lake; however, stations having these profiles did not have higher groundwater flow than other sites sampled. Alternate explanations for the HSD profiles were that the region in which they occurred had: (1) unusual sediment chemical compositions; (2) a different source of regional groundwater, or (3) a lateral intrusion of high SO42- groundwater. There were no differences in sulphide and organic matter concentrations between the two regions. The area which has HSD in the sediment covers a large area in the middle of the lake, so it is unlikely that it has a unique source of regional groundwater. The third alternative was supported by the fact that in all three sample years, HSD stations were located in the preimpoundment stream channel, which is a likely lateral flow path for groundwater containing high SO42- concentrations.  相似文献   

9.
While it remains the primary source of safe drinking and irrigation water in northwest Iran's Maku Plain, the region's groundwater is prone to fluoride contamination. Accordingly, modeling techniques to accurately predict groundwater fluoride concentration are required. The current paper advances several novel data mining algorithms including Lazy learners [instance-based K-nearest neighbors (IBK); locally weighted learning (LWL); and KStar], a tree-based algorithm (M5P), and a meta classifier algorithm [regression by discretization (RBD)] to predict groundwater fluoride concentration. Drawing on several groundwater quality variables (e.g., concentrations), measured in each of 143 samples collected between 2004 and 2008, several models predicting groundwater fluoride concentrations were developed. The full dataset was divided into two subsets: 70% for model training (calibration) and 30% for model evaluation (validation). Models were validated using several statistical evaluation criteria and three visual evaluation approaches (i.e., scatter plots, Taylor and Violin diagrams). Although Na+ and Ca2+ showed the greatest positive and negative correlations with fluoride (r = 0.59 and −0.39, respectively), they were insufficient to reliably predict fluoride levels; therefore, other water quality variables, including those weakly correlated with fluoride, should be considered as inputs for fluoride prediction. The IBK model outperformed other models in fluoride contamination prediction, followed by KStar, RBD, M5P, and LWL. The RBD and M5P models were the least accurate in terms of predicting peaks in fluoride concentration values. Results of the current study can be used to support practical and sustainable management of water and groundwater resources.  相似文献   

10.
A heterogeneous chemical model is developed by coupling aerosol, gas-phase and liquid-phase chemical model. SO2 oxidation rates on the aerosol surface are calculated and the influence of some factors is discussed. Model simulations indicate that SO2 heterogeneous oxidation rates are sensitive to the mass concentration and chemical composition of aerosols, relative humidity, initial values of SO2 and H2O2. The heterogeneous chemical model is coupled with a Eulerian deposition model. Model results show that oxidation of SO2 on the aerosol surface is found to reduce SO2 levels by 5%–33%, to increase SO 4 2- - concentrations by 8%–50% in the surface layer. Project supported by the National “85-912” Key Science and Technology Project.  相似文献   

11.
In this study, three approaches namely parallel, sequential, and multiple linear regression are applied to analyze the local air quality improvements during the COVID-19 lockdowns. In the present work, the authors have analyzed the monitoring data of the following primary air pollutants: particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO). During the lockdown period, the first phase has most noticeable impact on airquality evidenced by the parallel approach, and it has reflected a significant reduction in concentration levels of PM10 (27%), PM2.5 (19%), NO2 (74%), SO2 (36%), and CO (47%), respectively. In the sequential approach, a reduction in pollution levels is also observed for different pollutants, however, these results are biased due to rainfall in that period. In the multiple linear regression approach, the concentrations of primary air pollutants are selected, and set as target variables to predict their expected values during the city's lockdown period.The obtained results suggest that if a 21-days lockdown is implemented, then a reduction of 42 µg m−3 in PM10, 23 µg m−3 in PM2.5, 14 µg m−3 in NO2, 2 µg m−3 in SO2, and 0.7 mg m−3 in CO can be achieved.  相似文献   

12.
Assessing the long-term benefits of marginal improvements in air quality from regulatory intervention is methodologically challenging. In this study, we explore how the relative risks (RRs) of mortality from air pollution exposure change over time and whether patterns in the RRs can be attributed to air quality improvements. We employed two-stage multilevel Cox models to describe the association between air pollution and mortality for 51 cities with data from the American Cancer Society (ACS) cohort (N = 264,299, deaths = 69,819). New pollution data were computed through models that predict yearly average fine particle (PM2.5) concentrations throughout the follow-up (1982–2000). Average PM2.5 concentrations from 1999 to 2000 and sulfate concentrations from 1980 were also examined. We estimated the RRs of mortality associated with air pollution separately for five time periods (1982–1986, 1987–1990, 1991–1994, 1995–1998, and 1999–2000). Mobility models were implemented with a sub-sample of 100,557 subjects to assist with interpreting the RR estimates. Sulfate RRs exhibit a large decline from the 1980s to the 1990s. In contrast, PM2.5 RRs follow the opposite pattern, with larger RRs later in the 1990s. The reduction in sulfate RR may have resulted from air quality improvements that occurred through the 1980s and 1990s in response to the acid rain control program. PM2.5 concentrations also declined in many places, but toxic mobile sources are now the largest contributors to PM in urban areas. This may account for the heightened RR of mortality associated with PM2.5 in the 1990s. The paper concludes with a three alternative explanations for the temporal pattern of RRs, each emphasizing the uncertainty in ascribing health benefits to air quality improvements.  相似文献   

13.
Global marine vessels emissions are adversely affecting human health particularly in southeast Asia. But health burdens from both ocean- and river-going vessels in Pearl River Delta (PRD) regions are not quantified. We estimated the potential health impacts using pooled relative risks of mortality and hospital admissions in China, and the model derived concentrations of sulfur dioxide (SO2), particulate matter (PM10), nitrogen dioxide (NO2) and ozone (O3) due to vessels emissions. SO2 concentrations due to marine emissions in Hong Kong were 13.6 μgm?3 compared with 0.7 μgm?3 in PRD regions that were far from the marine vessels. In PRD regions, the estimated annual numbers (per million people) of excess deaths from all natural causes and hospital admissions from cardiorespiratory causes attributable to SO2, NO2, O3 and PM10 combined from marine emissions were 45 and 265 respectively. Marine emission control measures could contribute a large reduction in mortality and hospital admissions in PRD regions especially in Hong Kong.  相似文献   

14.
Presently available data on the reaction of SO2 with OH radicals (OH + SO2 + \(M\xrightarrow[{k_1 }]{}\) HSO3 +M) are critically reviewed in light of recent stratospheric sulfur budget calculations. These calculations impose that the net oxidation ratek of SO2 within the stratosphere should fall within the range 10?7≤k≤10?9, if the SO2 oxidation model for the stratospheric sulfate layer is assumed to be correct. The effective reaction rate constantk 1 * =k 1[M] at the stratospheric temperature is estimated as $$k_1^* = \frac{{(8.2 \pm 2.2) \times 10^{ - 13} \times [M]}}{{(0.79 \mp 0.34) \times 10^{ - 13} + [M]}}cm^3 /molecules sec$$ where [M] refers to the total number density (molecules/cm3). Using the above limiting values ofk 1 * , and the estimated OH density concentrations, the net oxidation rate is calculated as 3.6×10?7≤k≤1.3×10?8 at 17 km altitude. This indicates that the upper limit of thesek values exceeds the tolerable range imposed by the model by a factor of about four. Obviously the uncertainty of thek 1 * values and of the OH concentrations in the stratosphere is still too large to make definite conclusions on the validity of the SO2 model.  相似文献   

15.
Field surveys on atmospheric deposition and stream water chemistry were conducted in an evergreen forest in northeastern Thailand characterized by a tropical savanna climate with distinct dry and wet seasons. Atmospheric deposition of ion constituents by throughfall and stemflow was shown to increase in the beginning and end of the wet season, reflecting the precipitation pattern. The pH and electrical conductivity of stream water increased with alkalinity and base cation concentrations due to mineralization of organic matter by the first rain and retention of anions in soil during the start of the wet season. After initial alkalinization, the pH and alkalinity declined rapidly with the highest SO42? concentration displayed in the middle towards the end of the wet season. The magnitude of peaks in SO42? concentration (13.5–60.6 μmolc/L) reflects deposition during the first 2 months of the wet season (March and April) in respective years (60.8–170 molc/ha). Release of SO42? with H+, which is retained in soil during the early wet season, may cause acidification later in the season. The deposition and concentration of SO42? declined over 6 years. However, the pH of stream water declined with increasing concentrations of SO42? and other major ions. The release of materials accumulated in the ecosystem was facilitated by the decrease in SO42? concentration/deposition and increased precipitation in the middle–late wet season. The retention‐release cycle of SO42? largely contributed to both seasonal and interannual variations in stream water chemistry in the tropical savanna climate studied.  相似文献   

16.
In this study, seven types of first‐order and one‐variable grey differential equation model (abbreviated as GM (1, 1) model) were used to forecast hourly roadside particulate matter (PM) including PM10 and PM2.5 concentrations in Taipei County of Taiwan. Their forecasting performance was also compared. The results indicated that the minimum mean absolute percentage error (MAPE), mean squared error (MSE), root mean squared error (RMSE), and maximum correlation coefficient (R) was 11.70%, 60.06, 7.75, and 0.90%, respectively when forecasting PM10. When forecasting PM2.5, the minimum MAPE, MSE, RMSE, and maximum R‐value of 16.33%, 29.78, 5.46, and 0.90, respectively could be achieved. All statistical values revealed that the forecasting performance of GM (1, 1, x(0)), GM (1, 1, a), and GM (1, 1, b) outperformed other GM (1, 1) models. According to the results, it revealed that GM (1, 1) was an efficiently early warning tool for providing PM information to the roadside inhabitants.  相似文献   

17.
Contamination by the pollutants SO2 and SO=4 was analyzed for the 1989–1992 period at four regional stations in Spain under the auspices of the EMEP-BAPMON program. The evolution of the time series of the daily pollution has also been assessed, and high mean concentrations at La Cartuja and Logroño observed, with values of 3.8 and 4.5 g m−3 for SO2, respectively. Maximum annual concentrations were recorded in 1989, when SO2 reached values of 6.24, 5.39, 5.71, and 9.30 g m−3 for the stations of La Cartuja, San Pablo de los Montes, Roquetas, and Logroño, respectively. This work attempts to establish a relationship between the concentrations of the pollutants - both SO2 gas and SO=4 aerosol - and the zones of emission or persistence of these long-range transported pollutants. In this way, those regions showing a greater impact on the air quality in each season have been determined. To achieve this, the trajectories of the air masses carrying away the pollution to each of the receiving stations were considered and followed by a sectorial analysis. Nonparametric statistical methods were implemented to contrast the chemical homogeneity among the different sectors. The criterion that several homogeneous sectors form a chemically homogeneous region was used. To improve this sectorial analysis, we have proposed a new technique based on the Potential-Source-Contribution Function (PSCF). Starting out from a set of specified regions, considered to be chemically homogeneous domains, it is possible to determine the likelihood that an air mass with particular characteristics (e.g., that a value of the daily concentration higher than the mean recorded at the station has been obtained) will arrive at a given station after having crossed one of the previously defined regions. Using this technique, it is possible to determine the source regions through which the air masses circulate and bring high pollution concentrations to the studied stations. Thanks to the PSCF, these statistical methods offer, through a sectorial analysis, the possibility to pass from a qualitative to a more quantitative view.  相似文献   

18.
Groundwater is an especially important freshwater source for water supplies in the Maku area of northwest Iran. The groundwater of the area contains high concentrations of fluoride and is, therefore, important in predicting the fluoride contamination of the groundwater for the purpose of planning and management. The present study aims to evaluate the ability of the extreme learning machine (ELM) model to predict the level of fluoride contamination in the groundwater in comparison to multilayer perceptron (MLP) and support vector machine (SVM) models. For this purpose, 143 water samples were collected in a five-year period, 2004–2008. The samples were measured and analyzed for electrical conductivity, pH, major chemical ions and fluoride. To develop the models, the data set—including Na+, K+, Ca2+ and HCO3 ? concentrations as the inputs and fluoride concentration as the output—was divided into two subsets; training/validation (80% of data) and testing (20% of data), based on a cross-validation technique. The radial basis-based ELM model resulted in an R 2 of 0.921, an NSC of 0.9071, an RMSE of 0.5638 (mg/L) and an MABE of 0.4635 (mg/L) for the testing data. The results showed that the ELM models performed better than MLP and SVM models for prediction of fluoride contamination. It was observed that ELM models learned faster than the other models during model development trials and the SVM models had the highest computation time.  相似文献   

19.
Data from a series of laboratory experiments show the relationships between measured correlation spectrometer (COSPEC) sulfur-dioxide (SO2) burdens, automatic gain control (AGC) deflections, and visible wavelength opacities in ash-laden plumes. The data show that the COSPEC reliably measures (within a 10% accuracy) SO2 burdens up to AGC deflections of 2 V and visible wavelength opacities of 50%. Beyond these limits, the under measurement of the SO2 burden is not well constrained. During typical COSPEC runs, these limits are rarely violated. The 10% error introduced by measuring ash-laden plumes is acceptable because the error is small relative to other error sources associated with the technique, especially plume velocity; and the error is correctable which allows for a wider range of plume conditions to be measured.These results imply that the densest SO2 concentrations near the volcanic source can be measured. This is important so that SO2 is not lost from the volcanic plume due to physical and chemical processes and that measurements are conducted under maximum signal to noise ratios.  相似文献   

20.
Volcán Fuego in the Central American Republic of Guatemala erupted violently in October, 1974. A remote sensing correlation spectrometer. COSPEC IV, which utilizes the characteristic molecular absorption of SO2 in the ultraviolet was used to monitor the SO2 content of the volcanic plume. Over a 60-day period measurements were made on 37 days between and following major eruptive phases. SO2 emission rates corrected for atmospheric scattering of the spectral signal average 423 metric tons/day with a standard deviation of 252 metric tons/days. Late stage peaks in SO2 emission at Fuego are consistent with the presence of anomalously high contents of soluble materials on the stratigraphically highest ashes from other Central American eruptions. Indications are that the SO2 concentration within the volcanic plume increased as activity waned. These features imply that remote spectroscopic sensing of SO2 and perhaps other gases in a volcanic plume may provide a relatively easy and inexpensive means of determining the cessation of violent eruptive activity.  相似文献   

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