Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India

The objective of the study is to investigate seasonal and spatial variations of PM₁₀ (particulate matter with aerodynamic diameter less than or equal to 10 μm) and TSP (total suspended particulate matter) of an Indian Metropolis with high pollution and population density from November 2003 to November 2004. Ambient concentration measurements of PM₁₀ and TSP were carried out at two monitoring sites of an urban region of Kolkata. Monitoring sites have been selected based on the dominant activities of the area. Meteorological parameters such as wind speed, wind direction, rainfall, temperature and relative humidity were also collected simultaneously during the sampling period from Indian Meteorological Department, Kolkata. The 24 h average concentrations of PM₁₀ and TSP were found in the range 68.2–280.6 μg/m³ and 139.3–580.3 μg/m³ for residential (Kasba) area, while 62.4–401.2 μg/m³ and 125.7–732.1 μg/m³ for industrial (Cossipore) area, respectively. Winter concentrations of particulate pollutants were higher than other seasons, irrespective of the monitoring sites. It indicates a longer residence time of particulates in the atmosphere during winter due to low winds and low mixing height. Spread of air pollution sources and non-uniform mixing conditions in an urban area often result in spatial variation of pollutant concentrations. The higher particulate pollution at industrial area may be attributed due to resuspension of road dust, soil dust, automobile traffic and nearby industrial emissions. Particle size analysis result shows that PM₁₀ is about 52% of TSP at residential area and 54% at industrial area.     

Seasonal Variation of the Particle Size Distribution of n-Alkanes and Polycyclic Aromatic Hydrocarbons (PAHs) in Urban Aerosol of Guangzhou, China

Seasonal aerosol samples have been collected by Andersen Hi-Vol pumping system equipped with a five stage cascade impactor and a backup filter (size range: 10–7.2 μ m, 7.2–3.0 μ m, 3.0–1.5 μ m, 1.5–0.95 μ m, 0.95–0.49 μ m, ≤0.49 μ m) in the Liwan district, Guangzhou. n-Alkanes were measured using gas chromatography and PAHs were measured using gas chromatography/mass spectrometry analysis. The bimodal log-normal distributions of n-alkanes and semi-volatile PAHs were found, while for non-volatile PAHs that was unimodal, so much as the mode of semi-volatile PAHs was similar with that of the particles. The n-alkanes and PAHs were preferably associated with fine particles. C _max (carbon number maximum) (C₂₂–C₂₆), CPI (carbon preference index) (1.12–1.21), U/R (unresolved to resolved components ratio) (7.42–10.7), wax% (0.9–3.12%) and the diagnostic ratios for PAHs revealed that vehicular emission was the major source of these organic compounds during the study periods, while the contribution of epicuticular waxes emitted by terrestrial plants was minor. CPI₂ (values for petrogenic hydrocarbons), CPI₃ (values for biogenic n-alkanes) and wax% revealed that the natural preferentially accumulated in the larger aerosol while the anthropogenic in the smaller. In addition, the different MMDs (mass median diameters) for n-alkanes and PAHs were observed in different seasons. The MMDs for n-alkanes and PAHs were higher in autumn/winter than those in spring/summer. The seasonal effect was related to the hydrocarbon content in the individual particulate fractions, showing a preferential association of n-alkanes and PAHs with larger particles in the autumn/winter season.     

General plume dispersion model (GPDM) for point source emission

Gaussian-based dispersion models are widely used to estimate local pollution levels. The accuracy of such models depends on stability classification schemes as well as plume rise equations. A general plume dispersion model (GPDM) for a point source emission, based on Gaussian plume dispersion equation, was developed. The program complex was developed using Java and Visual basic tools. It has the flexibility of using five kinds of stability classification schemes, i.e., Lapse Rate, Pasquill–Gifford (PG), Turner, σ–θ and Richardson number. It also has the option of using two types of plume rise formulations – Briggs and Holland’s. The model, applicable for both rural and urban roughness conditions, uses meteorological and emission data as its input parameters, and calculates concentrations of pollutant at the center of each cell in a predefined grid area with respect to the given source location. Its performance was tested by comparing with 4-h average field data of continuous releases of SO₂ from Dadri thermal power plant (Uttar Pradesh, India). Results showed that the Turner scheme used with Holland’s equation gives the best outcome having a degree of agreement (d) of 0.522.     

Sources of PM10 and PM2.5 in Cairo’s ambient air

A source attribution study was performed to assess the contributions of specific pollutant source types to the observed particulate matter (PM) levels in the greater Cairo Area using the chemical mass balance (CMB) receptor model. Three intensive ambient monitoring studies were carried out during the period of February 21–March 3, 1999, October 27–November 27, 1999, and June 8–June 26, 2002. PM₁₀, PM_2.5, and polycyclic aromatic hydrocarbons (PAHs) were measured on a 24-h basis at six sampling stations during each of the intensive periods. The six intensive measurement sites represented background levels, mobile source impacts, industrial impacts, and residential exposure. Major contributors to PM₁₀ included geological material, mobile source emissions, and open burning. PM_2.5 tended to be dominated by mobile source emissions, open burning, and secondary species. This paper presents the results of the PM₁₀ and PM_2.5, source contribution estimates.     

Hybrid Neural Networks and Boosted Regression Tree Models for Predicting Roadside Particulate Matter

This paper examines the application of artificial neural network (ANN) and boosted regression tree (BRT) methods in air quality modelling. The methods were applied to developing air quality models for predicting roadside particle mass concentration (PM₁₀, PM_2.5) and particle number counts (PNC) based on air pollution, traffic and meteorological data from Marylebone Road in London. Elastic net, Lasso and principal components analysis were used as feature selection methods for the ANN models to reduce the number of predictor variables and improve their generalisation. The performance of the ANN with feature selection (ANN hybrid) and the BRT models was evaluated and compared using statistical performance metrics. The performance parameters include root mean square error (RMSE), fraction of prediction within a factor of two of the observation (FAC2), mean bias (MB), mean gross error (MGE), the coefficient of correlation (R) and coefficient of efficiency (CoE) values. The input variables selected by the elastic net produced the best performing ANN models. The ANN hybrid produced models performed only slightly better than the BRT models. The R values of the ANN elastic net and BRT models were 0.96 and 0.95 for PM₁₀, 0.96 and 0.96 for PM_2.5 and 0.89 and 0.87 for PNC, respectively. Their corresponding CoE values were 0.72 and 0.70 for PM₁₀, 0.74 and 0.76 for PM_2.5 and 0.81 and 0.71 for PNC respectively. About 80–99% of all the model predictions are within a factor of two of the observed particle concentrations. The BRT models offer more advantages regarding model interpretation and permit feature selection. Therefore, the study recommends the use of BRT over ANN where the model interpretation is a priority.     

Determination of road dust loadings and chemical characteristics using resuspension

The contribution of fugitive dust from traffic to air pollution can no longer be ignored in China. In order to obtain the road dust loadings and to understand the chemical characteristics of PM₁₀ and PM_2.5 from typical road dust, different paved roads in eight districts of Beijing were selected for dust collection during the four seasons of 2005. Ninety-eight samples from 28 roads were obtained. The samples were resuspended using equipment assembled to simulate the rising process of road dust caused by the wind or wheels in order to obtain the PM₁₀ and PM_2.5 filter samples. The average road dust loading was 3.82 g m^− 2, with the highest of 24.22 g m^− 2 being in Hutongs in the rural–urban continuum during winter. The road dust loadings on higher-grade roads were lower than those on lower-grade roads. Attention should be paid to the pollution in the rural–urban continuum areas. The sums of element abundances measured were 16.17% and 18.50% for PM₁₀ and PM_2.5 in road dust. The average abundances of OC and EC in PM₁₀ and PM_2.5 in road dust were 11.52%, 2.01% and 12.50%, 2.06%, respectively. The abundance of elements, water-soluble ions, and OC, EC in PM₁₀ and PM_2.5 resuspended from road dust did not change greatly with seasons and road types. The soil dust, construction dust, dust emitted from burning coal, vehicle exhaust, and deposition of particles in the air were the main sources of road dust in Beijing. Affected by the application of snow-melting agents in Beijing during winter, the amount of Cl⁻ and Na⁺ was much higher during that time than in the other seasons. This will have a certain influence on roads, bridges, vegetations, and groundwater.     

Characterisation of PM10, PM2.5 and Benzene Soluble Organic Fraction of Particulate Matter in an Urban Area of Kolkata, India

In this study, the relationship between inhalable particulate (PM₁₀), fine particulate (PM_2.5), coarse particles (PM_{2.5 – 10}) and meteorological parameters such as temperature, relative humidity, solar radiation, wind speed were statistically analyzed and modelled for urban area of Kolkata during winter months of 2003–2004. Ambient air quality was monitored with a sampling frequency of twenty-four hours at three monitoring sites located near traffic intersections and in an industrial area. The monitoring sites were located 3–5 m above ground near highly trafficked and congested areas. The 24 h average PM₁₀ and PM_2.5 samples were collected using Thermo-Andersen high volume samplers and exposed filter papers were extracted and analysed for benzene soluble organic fraction. The ratios between PM_2.5 and PM₁₀ were found to be in the range of 0.6 to 0.92 and the highest ratio was found in the most polluted urban site. Statistical analysis has shown a strong positive correlation between PM₁₀ and PM_2.5 and inverse correlation was observed between particulate matter (PM₁₀ and PM_2.5) and wind speed. Statistical analysis of air quality data shows that PM₁₀ and PM_2.5 are showing poor correlation with temperature, relative humidity and solar radiation. Regression equations for PM₁₀ and PM_2.5 and meteorological parameters were developed. The organic fraction of particulate matter soluble in benzene is an indication of poly aromatic hydrocarbon (PAH) concentration present in particulate matter. The relationship between the benzene soluble organic fraction (BSOF) of inhalable particulate (PM₁₀) and fine particulate (PM_2.5) were analysed for urban area of Kolkata. Significant positive correlation was observed between benzene soluble organic fraction of PM₁₀ (BSM10) and benzene soluble organic fraction of PM_2.5 (BSM2.5). Regression equations for BSM10 and BSM2.5 were developed.     

Air quality at a snowmobile staging area and snow chemistry on and off trail in a Rocky Mountain subalpine forest, Snowy Range, Wyoming

A study was begun in the winter of 2000–2001 and continued through the winter of 2001–2002 to examine air quality at the Green Rock snowmobile staging area at 2,985 m elevation in the Snowy Range of Wyoming. The study was designed to evaluate the effects of winter recreation snowmobile activity on air quality at this high elevation site by measuring levels of nitrogen oxides (NO _x , NO), carbon monoxide (CO), ozone (O₃) and particulate matter (PM₁₀ mass). Snowmobile numbers were higher weekends than weekdays, but numbers were difficult to quantify with an infrared sensor. Nitrogen oxides and carbon monoxide were significantly higher weekends than weekdays. Ozone and particulate matter were not significantly different during the weekend compared to weekdays. Air quality data during the summer was also compared to the winter data. Carbon monoxide levels at the site were significantly higher during the winter than during the summer. Nitrogen oxides and particulates were significantly higher during the summer compared to winter. Nevertheless, air pollutants were well dispersed and diluted by strong winds common at the site, and it appears that snowmobile emissions did not have a significant impact on air quality at this high elevation ecosystem. Pollutant concentrations were generally low both winter and summer. In a separate study, water chemistry and snow density were measured from snow samples collected on and adjacent to a snowmobile trail. Snow on the trail was significantly denser and significantly more acidic with significantly higher concentrations of sodium, ammonium, calcium, magnesium, fluoride, and sulfate than in snow off the trail. Snowmobile activity had no effect on nitrate levels in snow.     

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

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

Do the pollution related to high-traffic roads in urbanised areas pose a significant threat to the local population?

Many large neighbourhoods are located near heavy-traffic roads; therefore, it is necessary to control the levels of air pollution near road exposure. The primary air pollutants emitted by motor vehicles are CO, NO₂ and PM. Various investigations identify key health outcomes to be consistently associated with NO₂ and CO. The objective of this study was the measurement-based assessment for determining whether by high-traffic roads, such as motorways and express ways, and the concentrations of CO and NO₂ are within normal limits and do not pose threat to the local population. Average daily values (arithmetic values calculated for 1-h values within 24 h or less, depending on result availability) were measured for concentrations of NO₂ and CO by automatic stations belonging to the Voivodship Environmental Protection Inspectorate in Katowice, in areas with similar dominant source of pollutant emission. The measurements were made in three sites: near the motorway and expressway, where the average daily traffic intensity is 100983 and 35414 of vehicles relatively. No evidence was found of exceeding average daily values equal to the maximum allowable NO₂ concentration due to the protection of human health in the measurement area of the stations. No daily average values exceeding the admissible CO concentration (8-h moving average) were noted in the examined period. The results clearly show lack of hazards for general population health in terms of increased concentrations of CO and NO₂ compounds that are closely related to high intensity car traffic found on selected motorways and speedways located near the city centres.     

Modified grey model for estimating traffic tunnel air quality

This study compared three forecasting models based on the mean absolute percentage errors (MAPE) of their accuracy in forecasting air pollution in a traffic tunnel: the Grey model (GM), the combination model used four sample point and five sample point prediction with GM (1,1)(GM(1,1)^4 + 5), and the modified grey model (MGM). An MGM was combined using the four points of the original sequence using the original grey prediction GM (1,1) for short-term forecasting. The proposed method cannot only enhance the prediction accuracy of the original grey model, but can also solve the jump data forecasting problem something for which the original grey model is inappropriate. The MAPE was applied to the models, and the MGM found the proposed method to be simple and efficient. The MAPE of MGM, calculated over 3 h of forecasts, were as follows: 10.12 (Upwind), 10.07 (Middle) and 7.68 (Downwind) for CO; 10.79 (Upwind), 6.05 (Middle) and 5.98 (Downwind) for NO _x , and 11.67 (Upwind), 7.32 (Middle) and 4.56 (Downwind) for NMHC. The MGM model results reveal that the combined forecasts can significantly decrease the overall forecasting error. Results of this demonstrate that MGM can accurately forecast air pollution in the Kaohsiung Chung–Cheng Tunnel.     

Ambient Aerosol and its Carbon Content in Gainesville, a Mid-Scale City in Florida

Ambient aerosols were collected during 2000–2001 in Gainesville, Florida, using a micro-orifice uniform deposit impactor (MOUDI) to study mass size distribution and carbon composition. A bimodal mass distribution was found in every sample with major peaks for aerosols ranging from 0.32 to 0.56 μm, and 3.2 to 5.6 μm in diameter. The two distributions represent the fine mode (<2.5 μm) and the coarse mode (>2.5 μm) of particle size. Averaged over all sites and seasons, coarse particles consisted of 15% carbon while fine particles consisted of 22% carbon. Considerable variation was noted between winter and summer seasons. Smoke from fireplaces in winter appeared to be an important factor for the carbon, especially the elemental carbon contribution. In summer, organic carbon was more abundant. The maximum secondary organic carbon was also found in this season (7.0 μg m⁻³), and the concentration is between those observed in urban areas (15–20 μg m⁻³) and in rural areas (4–5 μg m⁻³). However, unlike in large cities where photochemical activity of anthropogenic emissions are determinants of carbon composition, biogenic sources were likely the key factor in Gainesville. Other critical factors that affect the distribution, shape and concentration were precipitation, brushfire and wind.     

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).     

Carbon monoxide concentrations in Santiago City at street levels and their vertical gradient

Carbon monoxide concentrations were measured at ground level (1 m) near heavy traffic streets in downtown Santiago de Chile in periods of low (November and December), intermediate (April) and high (May) ambient concentrations. Also, measurements were carried out at several heights (from 1 to 127 m) in Santiago’s main street during winter time. Measurements carried out at ground level show maximum values during the morning rush hour, with values considerably higher than those reported by the urban air quality network, particularly in summer time. However, the measured values are below air quality standards. Vertical CO profiles were measured in a tower located in the center of downtown. Below 40 m (average altitude of neighboring buildings), the profiles do not show a consistent vertical gradient, with CO concentrations increasing or decreasing with height, regardless of atmospheric stability. In this low altitude range, the observed vertical profiles are poorly predicted by a street canyon model, and the measured concentrations can not be described by a simple exponential decay. At higher altitudes (40 and 127 m) a negative gradient in CO concentrations is observed, both for stable and unstable atmospheric conditions. The values of CO measured at 127 m are relatively well described by an Eulerian dispersion model running with current CO emission inventories for Santiago, although this model tends to predict stepper CO gradients than the observed ones.     

Effects of Cadmium (CdCl2) on development and hatching of eggs in European squid (Loligo vulgaris Lamarck, 1798) (Cephalopoda: Loliginidae)

This is the first study related to the effects of cadmium (Cd) on the development and hatching of eggs of Loligo vulgaris. The eggs were exposed to concentrations varying from 10 to 100,000 μg Cd/l for up to 1 month. During the study period natural sea water salinity (37 PSU), ambient temperature (ranging 16.5–21.5°C) and light conditions of 12-h light: 12-h dark for 744-h were used prior to the hatching. For 96-h, mortality rate of 100% of the eggs was found at cadmium concentration of 100,000 μg Cd/l, and the same mortality rate of the eggs were found at 1,000 and 10,000 μg Cd/l for 744-h and 696-h, respectively. Hatching took place between hours 456 and 576 in the control group and between hours 480 and 576 in 10 and 100 μg Cd/l groups. Total hatching rates were calculated to be 98.2 ± 1.6% for control group, 99.4 ± 0.6% for 10 μg Cd/l group and 98.6 ± 1.2% for 100 μg Cd/l group. Hatching successes were estimated as 69.5 ± 13.8% for control group, 84.5 ± 8.2% for 10 μg Cd/l group and 76.9 ± 5.9% for 100 μg Cd/l group. In the 100,000 μg Cd/l treatment, the egg degeneration began from animal pole of the eggs in 16 h, and 50% and 100% of them died in the initial stage at 72-h and 96-h, respectively. In the 10,000 μg Cd/l group, the eggs which reached at stage 19 (IX) were deformed and 50% and 100% of them died at 312-h and 696-h, respectively. In 1,000 μg Cd/l group, however, the eggs developed abnormally from stage 21 (X–XI) and reached at stage 29 (XIX), and 50% and 100% of them died in 624-h and in 744-h, respectively. There were significant differences in survival rates of the eggs among the concentrations (p < 0.05). The current study demonstrated that Cd adversely affects the development, survival and hatching of L. vulgaris eggs; however, no mortality was observed in 10 μg Cd/l and 100 μg Cd/l groups.     

Quantifying coastal inundation vulnerability of Turkey to sea-level rise

The vulnerability of low-lying coastal areas in Turkey to inundation was quantified based on the sea-level rise scenarios of 1, 2, and 3 m by 2205. Through digital elevation model (DEM) acquired by the shuttle radar topography mission (SRTM), the extent and distribution of the high to low-risk coastal plains were identified. The spatio-temporal analysis revealed the inundated coastal areas of 545, 1,286, and 2,125 km² at average rates of 5, 10, and 15 mm yr⁻¹ for 200 years, respectively. This is equivalent to minimum and maximum land losses by 2205 of 0.1–0.3% of the total area and of 1.3–5.2% of the coastal areas with elevations of less than 100 m in the country, respectively. This study provides an initial assessment of vulnerability to sea-level rise to help decision-makers, and other concerned stakeholders to develop appropriate public policies and land-use planning measures.     

Development of baseline (air quality) data in Pakistan

During 2003–2004, SUPARCO, the Pakistan Space and Upper Atmosphere Research Commission has conducted a year long baseline air quality study in country’s major urban areas (Karachi, Lahore, Quetta, Rawalpindi, Islamabad and Peshawar). The objective of this study was to establish baseline levels and behavior of airborne pollutants in urban centers with temporal and spatial parameters. This study reveals that the highest concentrations of CO were observed at Quetta (14 ppm) while other pollutants like SO₂ (52.5 ppb), NO _x (60.75 ppb) and O₃ (50 ppb) were higher at Lahore compared to other urban centers like Karachi, Peshawar etc. The maximum particulate (TSP) and PM10 levels were observed at Lahore (996 ug/m³ and 368 ug/m³ respectively), Quetta (778 ug/m³, 298 ug/m³) and in Karachi (410 ug/m³, 302 ug/m³). In all major cities the highest levels were recorded at major intersections and variations were directly correlated with traffic density. These pollutants showed highest levels in summer and spring while lowest were observed in winter and monsoon. A data bank has been generated for future planning and air pollution impact studies.     

Retrieval of total suspended matter (TSM) and chlorophyll-a (Chl-a) concentration from remote-sensing data for drinking water resources

The concentrations of chlorophyll-a (Chl-a) and total suspended matter (TSM) are major water quality parameters that can be retrieved using remotely sensed data. Water sampling works were conducted on 15 July 2007 and 13 September 2008 concurrent with the Indian Remote-Sensing Satellite (IRS-P6) overpass of the Shitoukoumen Reservoir. Both empirical regression and back-propagation artificial neural network (ANN) models were established to estimate Chl-a and TSM concentration with both in situ and satellite-received radiances signals. It was found that empirical models performed well on the TSM concentration estimation with better accuracy (R ² = 0.94, 0.91) than their performance on Chl-a concentration (R ² = 0.62, 0.75) with IRS-P6 imagery data, and the models accuracy marginally improved with in situ spectra data. Our results indicated that the ANN model performed better for both Chl-a (R ² = 0.91, 0.82) and TSM (R ² = 0.98, 0.94) concentration estimation through in situ collected spectra; the same trend followed for IRS-P6 imagery data (R ² = 0.75 and 0.90 for Chl-a; R ² = 0.97 and 0.95 for TSM). The relative root mean square errors (RMSEs) from the empirical model for TSM (Chl-a) were less than 15% (respectively 27.2%) with both in situ and IRS-P6 imagery data, while the RMSEs were less than 7.5% (respectively 18.4%) from the ANN model. Future work still needs to be undertaken to derive the dynamic characteristic of Shitoukoumen Reservoir water quality with remotely sensed IRS-P6 or Landsat-TM data. The algorithms developed in this study will also need to be tested and refined with more imagery data acquisitions combined with in situ spectra data.     

Estimation Of Selenium Concentration In Shallow Groundwater In Alluvial Fan Area In Tsukui, Central Japan

Total selenium (Se) and water-soluble Se in soil, and Se in a shallow groundwater were hydrogeochemically researched in an alluvial fan area in Tsukui, Central Japan. The water-soluble Se was estimated at average level of 2.6 ± 1.2μg Se kg⁻¹ dry soil (± SD, n = 25), showing less than 1% of the total Se (349–508μg Se kg⁻¹ dry soil) in soil. The monthly Se concentration in groundwater was average 2.2μg,L⁻¹, ranging 1.6–2.4μg,L⁻¹ during 2001–2003. The Se in groundwater significantly decreased with increasing groundwater level after rainfall. This result indicated that Se-bearing water percolated with relatively low Se concentration through the soil layer. According to our prediction model of linear regression curve on the observation data, Se concentration in the groundwater was estimated to be increasing with the very low rate of 4.35 × 10⁻³μg Se L⁻¹,yr⁻¹. The hydrogeochemical research and the result of the prediction model showed that any explosive increase of Se will hardly occur in this groundwater without an anthropogenic Se contamination.