scholarly journals Pollution Index and Air Ion Variation in Different Vegetation area at the Rural Station Bhilawadi (16059’N, 740 28’E)

2021 ◽  
Vol 1964 (3) ◽  
pp. 032006
Author(s):  
G B Patil ◽  
S D Pawar ◽  
J L Bhosale ◽  
P G Patil
Keyword(s):  
Pollution Index ◽  
Rural Station

scholarly journals Week Day and Week End Air Ion Variability at Rural station Ramanandnagar (17° 4’ N 74° 25’E), India and At Different Atmospheric Sites in India

2013 ◽  
Vol 13 (1) ◽  
pp. 65-73
Keyword(s):  
Urban Areas ◽  
Transition Period ◽  
Monsoon Season ◽  
Pollution Index ◽  
Negative Ion ◽  
Rural Station ◽  
Night Time ◽  
Post Monsoon ◽  
Post Monsoon Season ◽  
The Government

Globalization and liberalization polices of the government of India have increased the number of road vehicles nearly 92.6% from 1980-81 to 2003-2004. Therefore to know whether there is effect of increase of industrialization in the urban areas like Pune (18° 32′N, 73° 51′E); Mumbai (18° 55' N, 72° 54' E) and at rural station like Ramanandnagar (17° 4′ N, 74° 25′ E); pollution index is measured. Pollution index which is ratio of average positive to negative small air ion ratio is plotted for week days and week end. At the rural station like Ramanandnagar Monday to Saturday are working days, while Sunday is holiday. It is observed that ratio of average positive to negative small ion ratio is maximum for all time periods during the week day as compared to week end. The data have been collected during the period from first 1 June 2007 to 31 May 2008; the period under analysis involves 8,040 hours shows that the peak of the positive to negative small air ion ratio is observed in winter, and dip is observed in post-monsoon season. As Ramanandnagar is surrounded by vegetation area, therefore due to plant transpiration of Radon and Thoron small air ion maximum are observed at noon time rather than night time. During the week end positive small air ion count is low as compared to week days. While during week end negative small air ion count is very high as compared to week days, which is observed in all the seasons. Post-monsoon is the transition period during which few thunder storms are observed. Due to these thunder storms additional amount negative ion are introduced and positively charged aerosols are cleared from the atmosphere. Therefore in the post-monsoon negative small air ion count is high as compared to all other seasons. Such type of diurnal variation of small air ion detected at rural station Ramanandnagar has never been observed elsewhere.

Distribution and Contamination Status of Heavy Metals in the Surface Sediments along Western Coast of Bali Strait, Banyuwangi

2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Defri Yona ◽  
Syarifah Hikmah Julinda Sari ◽  
Anedathama Kretarta ◽  
Citra Ravena Putri Effendy ◽  
Misba Nur Aini ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Metal Pollution ◽  
Contamination Factor ◽  
Pollution Index ◽  
Western Coast ◽  
Sampling Locations ◽  
Accumulation Index ◽  
Geo Accumulation Index ◽  
Geo Accumulation

This study attempted to analyze the distribution and contamination status of heavy metals (Cu, Fe and Zn) along western coast of Bali Strait in Banyuwangi, East Java. Bali Strait is one of the many straits in Indonesia with high fisheries activities that could potentially contributed to high heavy metal pollution. There were five sampling areas from the north to south: Pantai Watu Dodol, Pantai Kalipuro, Ketapang Port, Pantai Boom and Muncar as the fish landing area. Heavy metal pollution in these locations comes from many different activities such as tourism, fish capture and fish industry and also domestic activities. Contamination factor (CF), geo-accumulation index (Igeo) and enrichment factor (EF) of each heavy metal were calculated to obtain contamination status of the research area. The concentrations of Fe were observed the highest (1.5-129.9 mg/kg) followed by Zn (13.2-23.5 mg/kg) and Cu (2.2-7.8 mg/kg). The distribution of Cu, Fe and Zn showed variability among the sampling locations in which high concentrations of Cu and Zn were higher in Ketapang Port, whereas high concentration of Fe was high in almost all sampling locations. According to the pollution index, contamination factors of Cu, Fe and Zn were low (CF < 1 and Igeo < 1). However, high index of EF (> 50) showed high influence of the anthropogenic activities to the contribution of the metals to the environment. This could also because of the high background value used in the calculation of the index due to the difficulties in finding background value from the sampling areas.Keywords: heavy metals, pollution index, contamination factor, geo-accumulation index, Bali Strait

Integrated assessment and mapping of the environmental situation in the Russian Federation regions

2017 ◽  
Vol 924 (6) ◽  
pp. 6-16
Author(s):  
V.S. Tikunov ◽  
O.Yu. Chereshnia
Keyword(s):  
Russian Federation ◽  
Pollution Index ◽  
Pollution Level ◽  
Anthropogenic Pressure ◽  
Environmental Capacity ◽  
Environmental Friendliness ◽  
Second Stage ◽  
Environmental Situation ◽  
The Russian Federation ◽  
Two Stages

The article presents a methodology for a comprehensive assessment of the environmental situation in Russian Federation regions based on the pollution index and the index of the ecological tension. The evaluation was carried out in two stages. At the first stage, the degree of pollution of the atmosphere, hydrosphere and lithosphere of the regions was estimated on the basis of the emission of pollutants into the atmosphere, departing from stationary sources, the formation of solid domestic wastes (SDW) and the discharge of contaminated wastewater. Based on these three indicators, a pollution index was constructed that estimates aggregate pollution level. In the second stage, the authors made the estimation of loads generated by atmospheric emissions, solid waste and waste water discharged into the territory of each region, per capita and in relation to the environmental capacity of the economy. This allows us to take into account the area of pollution, anthropogenic pressure and environmental responsibility of the population, as well as the environmental friendliness of production. On the basis of relative indicators, the index of ecological tension was created.

scholarly journals Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

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