scholarly journals Assimilative capacity of the atmosphere at Gorakhpur with respect to air pollution

MAUSAM ◽  
2022 ◽  
Vol 53 (4) ◽  
pp. 481-486
Author(s):  
P. K. NANDANKAR

The present study aims at seasonal and diurnal pollution potential at Gorakhpur in east Uttar Pradesh. To assess the pollution potential, meteorological data for five year period (1982-86) of Gorakhpur have been analyzed for four seasons viz; winter (December-February), summer (March-May), monsoon (June-September) and post monsoon (October-November). Season wise wind roses, stability, stability wind roses have been prepared and season wise diurnal variation of mixing height and ventilation coefficient have also been worked out. It is found that Gorakhpur has a better diffusion capacity in summer and poor in post monsoon followed by winter. Afternoon hours are better for vertical mixing. The winds are predominantly from southwest to west in all seasons except in monsoon when it blows from northeast to east. Based on this study, an appropriate location for industrialization has been suggested.

MAUSAM ◽  
2021 ◽  
Vol 50 (3) ◽  
pp. 263-268
Author(s):  
P .K. NANDANKAR

The present study aim at seasonal and diurnal pollution potential at Lucknow, the capital of Uttar Pradesh. To assess the pollution potential, meteorological data for five year period (1982-86) of Lucknow have been analyzed for four season, viz.; Winter (December-February), Summer (March-May), Southwest Monsoon (June-September) and Post Monsoon (October-November). Seasonwise wind roses, stability, stability wind roses have been prepared and season wise diurnal variation of mixing height and ventilation coefficient have also been worked out. It is found that Lucknow has a better diffusion capacity in summer and poor in winter. Afternoon hours are better for vertical mixing. The winds are predominant from west to north direction in all season except in monsoon where it blows from east direction.


MAUSAM ◽  
2022 ◽  
Vol 44 (2) ◽  
pp. 199-204
Author(s):  
BIJENDRA RAI

The present study aims at seasonal and diurnal pollution potential around Patna, the capital region of Bihar and Gaya. To assess the pollution potential, meteorological data of two stations, VIZ., Patna and the neighbouring station Gaya for five year period (1984-88) have been analysed; The analysis has been done for four representative seasonal months, viz., winter (January), pre-monsoon (April), monsoon (August) and post-monsoon (October).   The analysis shows no stable conditions in the day time and no unstable condition in the  night time in each month. April shows higher frequency and January the lowest frequencies of unstable conditions. April  has the highest mixing height and ventilation coefficient. From the results it has been concluded that day time is suitable for good dispersion in all the months. In the ca5e of existing industries, emission must be lessened during night time and particularly in the winter months. These results also suggest that pollutants are well dispersed in April and August. January and August may be regarded as the worst months for vertical diffusion of contaminants. As the predominant surface winds are easterly, any new Industrial set up should be in the west of the city in order to minimise the effects of pollutants.  


2020 ◽  
Vol 12 (21) ◽  
pp. 8932
Author(s):  
Kusum Pandey ◽  
Shiv Kumar ◽  
Anurag Malik ◽  
Alban Kuriqi

Accurate information about groundwater level prediction is crucial for effective planning and management of groundwater resources. In the present study, the Artificial Neural Network (ANN), optimized with a Genetic Algorithm (GA-ANN), was employed for seasonal groundwater table depth (GWTD) prediction in the area between the Ganga and Hindon rivers located in Uttar Pradesh State, India. A total of 18 models for both seasons (nine for the pre-monsoon and nine for the post-monsoon) have been formulated by using groundwater recharge (GWR), groundwater discharge (GWD), and previous groundwater level data from a 21-year period (1994–2014). The hybrid GA-ANN models’ predictive ability was evaluated against the traditional GA models based on statistical indicators and visual inspection. The results appraisal indicates that the hybrid GA-ANN models outperformed the GA models for predicting the seasonal GWTD in the study region. Overall, the hybrid GA-ANN-8 model with an 8-9-1 structure (i.e., 8: inputs, 9: neurons in the hidden layer, and 1: output) was nominated optimal for predicting the GWTD during pre- and post-monsoon seasons. Additionally, it was noted that the maximum number of input variables in the hybrid GA-ANN approach improved the prediction accuracy. In conclusion, the proposed hybrid GA-ANN model’s findings could be readily transferable or implemented in other parts of the world, specifically those with similar geology and hydrogeology conditions for sustainable planning and groundwater resources management.


1980 ◽  
Vol 7 (3) ◽  
pp. 241-244 ◽  
Author(s):  
Robert A. Preston-Whyte ◽  
Roseanne D. Diab

Atmospheric pollution over cities accumulates under light wind or stagnation conditions and, on occasion, may be supplemented by transport from distant sources. These conditions cannot easily be predicted by use of the average weather elements. However, material which is useful to decision-makers who are concerned with air pollution problems can be obtained by presenting the data, as in the case of Durban, South Africa, first in terms of the nature and characteristics of vertical mixing in the lower atmosphere, and secondly in terms of the horizontal transport of air. In this way the nature and characteristics of surface and non-surface inversions and mixingdepths, as well as of macro- and meso-scale atmospheric circulations, can more easily be appreciated. In addition, a measure of the air pollution potential can be obtained from daily maximum mixing-depth and win-speed values.


2005 ◽  
Vol 5 (5) ◽  
pp. 1187-1203 ◽  
Author(s):  
C. Ordóñez ◽  
H. Mathis ◽  
M. Furger ◽  
S. Henne ◽  
C. Hüglin ◽  
...  

Abstract. An Analysis of Covariance (ANCOVA) was used to derive the influence of the meteorological variability on the daily maximum ozone concentrations at 12 low-elevation sites north of the Alps in Switzerland during the four seasons in the 1992–2002 period. The afternoon temperature and the morning global radiation were the variables that accounted for most of the meteorological variability in summer and spring, while other variables that can be related to vertical mixing and dilution of primary pollutants (afternoon global radiation, wind speed, stability or day of the week) were more significant in winter. In addition, the number of days after a frontal passage was important to account for ozone build-up in summer and ozone destruction in winter. The statistical model proved to be a robust tool for reducing the impact of the meteorological variability on the ozone concentrations. The explained variance of the model, averaged over all stations, ranged from 60.2% in winter to 71.9% in autumn. The year-to-year variability of the seasonal medians of daily ozone maxima was reduced by 85% in winter, 60% in summer, and 50% in autumn and spring after the meteorological adjustment. For most stations, no significantly negative trends (at the 95% confidence level) of the summer medians of daily O3 or Ox (O3+NO2) maxima were found despite the significant reduction in the precursor emissions in Central Europe. However, significant downward trends in the summer 90th percentiles of daily Ox maxima were observed at 6 sites in the region around Zürich (on average −0.73 ppb yr-1 for those sites). The lower effect of the titration by NO as a consequence of the reduced emissions could partially explain the significantly positive O3 trends in the cold seasons (on average 0.69 ppb yr-1 in winter and 0.58 ppb yr-1 in autumn). The increase of Ox found for most stations in autumn (on average 0.23 ppb yr-1) and winter (on average 0.39 ppb yr-1) could be due to increasing European background ozone levels, in agreement with other studies. The statistical model was also able to explain the very high ozone concentrations in summer 2003, the warmest summer in Switzerland for at least ~150 years. On average, the measured daily ozone maximum was 15 ppb (nearly 29%) higher than in the reference period summer 1992–2002, corresponding to an excess of 5 standard deviations of the summer means of daily ozone maxima in that period.


Author(s):  
X. Zhao ◽  
L. Liu ◽  
X. Liu ◽  
Y. Zhao

Taking Xiamen city as the study area this research first retrieved surface net radiation using meteorological data and Landsat 5 TM images of the four seasons in the year 2009. Meanwhile the 65 different landscape metrics of each analysis unit were acquired using landscape analysis method. Then the most effective landscape metrics affecting surface net radiation were determined by correlation analysis, partial correlation analysis, stepwise regression method, etc. At both class and landscape levels, this paper comprehensively analyzed the temporal and spatial variations of the surface net radiation as well as the effects of land cover pattern on it in Xiamen from a multi-seasonal perspective. The results showed that the spatial composition of land cover pattern shows significant influence on surface net radiation while the spatial allocation of land cover pattern does not. The proportions of bare land and forest land are effective and important factors which affect the changes of surface net radiation all the year round. Moreover, the proportion of forest land is more capable for explaining surface net radiation than the proportion of bare land. So the proportion of forest land is the most important and continuously effective factor which affects and explains the cross-seasonal differences of surface net radiation. This study is helpful in exploring the formation and evolution mechanism of urban heat island. It also gave theoretical hints and realistic guidance for urban planning and sustainable development.


2016 ◽  
Vol 5 (2) ◽  
pp. 86-89
Author(s):  
SM Bari ◽  
SMI Khalil ◽  
MAA Mamun ◽  
MJ Islam ◽  
MA Baten ◽  
...  

A year round field investigations were conducted with the aim to examine the seasonal variation in population dynamics of helminth parasites in Clarias batrachus from different natural aquatic habitat of north-eastern region of Bangladesh, Sylhet. This article summarizes the percentage of prevalence, mean intensity, abundance and index of infestation of helminth parasites in the C. batrachus during different months and seasons of the year in accordance with temperature, humidity and rainfall. The investigation period were categorized into four seasons i.e. pre-monsoon (February-April), monsoon (May-July), post-monsoon (August- October) and winter (November- January). A total 180 C. batrachus host individuals were examined and among them 139 (67.87%) specimens were found to be infested with 2205 individuals of parasites of three different groups namely trematode, cestode and nematode. Almost (100%) prevalence of helminth infestation were recorded from both male and female C. batrachus during the winter (Nov-Jan), followed by (Feb-April) pre-monsoon (66.67-86.67%) and (Aug-Sep) post-monsoon (66.67-80.00%) while lowest (53.33-60.00%) in monsoon or rainy season (May-July). Lower range of environmental temperature (21.05–25.050C), associated with moderate humidity (62.00-64.00%) and scarcity of rainfall increases the intensity of helminthes parasitic infestation in C. batrachus. In consistent to this, with the gradual increasing in ambient temperature (28.01- 30.010C) and humidity (75.00-89.00%) associated with moderate rainfall (33.40-790.90 mm) declining the intensity of helminthes infestation in C. batrachus of the study area.International Journal of Natural Sciences (2015), 5(2) 86-89


2018 ◽  
Author(s):  
Katri Leino ◽  
Janne Lampilahti ◽  
Pyry Poutanen ◽  
Riikka Väänänen ◽  
Antti Manninen ◽  
...  

Abstract. This work presents airborne observations of sub-3 nm particles in the lower troposphere and investigates new particle formation (NPF) within an evolving boundary layer (BL). We studied particle concentrations together with supporting gas and meteorological data inside the planetary BL over a boreal forest site in Hyytiälä, Southern Finland. The analysed data were collected during three flight measurement campaigns: May–June 2015, August 2015 and April–May 2017, including 27 morning and 26 afternoon vertical profiles. As a platform for the instrumentation, we used a Cessna 172 aircraft. The analysed flight data were collected horizontally within a 30-km distance from the SMEAR II station in Hyytiälä and vertically from 100 metres above ground level up to 2700 m. The number concentration of 1.5–3 nm particles was observed to be, on average, the highest near the forest canopy top and to decrease with an increasing altitude during the mornings of NPF event days. This indicates that the precursor vapours emitted by the forest play a key role in NPF in Hyytiälä. During daytime, newly-formed particles were observed to grow in size and the particle population became more homogenous within the well-mixed BL in the afternoon. During undefined days in respect to NPF, we also detected an increase in concentrations of 1.5–3 nm particles in the morning but not their growth in size, which indicates an interrupted NPF process during these undefined days. Vertical mixing was typically stronger during the NPF event days than during the undefined or non-event days.


2008 ◽  
Vol 8 (4) ◽  
pp. 1017-1027 ◽  
Author(s):  
L. Järvi ◽  
H. Junninen ◽  
A. Karppinen ◽  
R. Hillamo ◽  
A. Virkkula ◽  
...  

Abstract. Variations in black carbon (BC) concentrations over different timescales, including annual, weekly and diurnal changes, were studied during ten years in Helsinki, Finland. Measurements were made in three campaigns between 1996 and 2005 at an urban area locating two kilometres of the centre of Helsinki. The first campaign took place from November 1996 to June 1997, the second from September 2000 to May 2001 and the third from March 2004 to October 2005. A detailed comparison between the campaigns was only made for winter and spring months when data from all campaigns existed. The effect of traffic and meteorological variables on the measured BC concentrations was studied by means of a multiple regression analysis, where the meteorological data was obtained from a meteorological pre-processing model (MPP-FMI). The BC concentrations showed annual pattern with maxima in fall and late winter due to the weakened mixing and enhanced emissions. Between 1996 and 2005, the campaign median BC concentrations decreased slightly from 1.11 to 1.00 μg m−3. The lowest campaign median concentration (0.93 μg m−3) was measured during the second campaign in 2000–2001, when also the lowest traffic rates were measured. The strongest decrease between Campaigns 1 and 3 was observed on weekday daytimes, when also the traffic rates are highest. The variables affecting the measured BC concentrations most were traffic, wind speed and mixing height. On weekdays, traffic had clearly the most important influence before the wind speed and on weekends the effect of wind speed diluted the effect of traffic. The affecting variables and their influence on the BC concentrations were similar in winter and spring. The separate examination of the three campaigns showed that the effect of traffic on the BC concentrations had decreased during the studied years. This reduction was caused by lower emitting vehicles, since between years 1996 and 2005 the traffic rates had increased.


2008 ◽  
Vol 8 (3) ◽  
pp. 591-602 ◽  
Author(s):  
C. Gerbig ◽  
S. Körner ◽  
J. C. Lin

Abstract. Imperfect representation of vertical mixing near the surface in atmospheric transport models leads to uncertainties in modelled tracer mixing ratios. When using the atmosphere as an integrator to derive surface-atmosphere exchange from mixing ratio observations made in the atmospheric boundary layer, this uncertainty has to be quantified and taken into account. A comparison between radiosonde-derived mixing heights and mixing heights derived from ECMWF meteorological data during May–June 2005 in Europe revealed random discrepancies of about 40% for the daytime with insignificant bias errors, and much larger values approaching 100% for nocturnal mixing layers with bias errors also exceeding 50%. The Stochastic Time Inverted Lagrangian Transport (STILT) model was used to propagate this uncertainty into CO2 mixing ratio uncertainties, accounting for spatial and temporal error covariance. Average values of 3 ppm were found for the 2 month period, indicating that this represents a large fraction of the overall uncertainty. A pseudo data experiment shows that the error propagation with STILT avoids biases in flux retrievals when applied in inversions. The results indicate that flux inversions employing transport models based on current generation meteorological products have misrepresented an important part of the model error structure likely leading to biases in the estimated mean and uncertainties. We strongly recommend including the solution presented in this work: better, higher resolution atmospheric models, a proper description of correlated random errors, and a modification of the overall sampling strategy.


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