Thermal Power Plant Emissions Research Articles

A Three-Wavelength Optical Sensor for Measuring the Multi-Particle-Size Channel Mass Concentration of Thermal Power Plant Emissions.

Emissions from thermal power plants have always been the central consideration for environmental protection. Existing optical sensors in thermal power plants usually measure the total mass concentration of the particulate matter (PM) by a single-wavelength laser, bearing intrinsic errors owing to the variation in particle size distribution (PSD). However, the total mass concentration alone cannot characterize all the harmful effects of the air pollution caused by the power plant. Therefore, it is necessary to measure the mass concentration and PSD simultaneously, based on which we can obtain multi-particle-size channel mass concentration. To achieve this, we designed an optical sensor based on the three-wavelength technique and tested its performance in a practical environment. Results showed that the prototype cannot only correctly measure the mass concentration of the emitted PM but also determine the mean diameter and standard deviation of the PSDs. Hence, the mass concentrations of PM10, PM2.5, and PM1 are calculated, and the air pollutants emission by a thermal power plant can be estimated comprehensively.

Role of an Ultra-Large Coal-Fired Power Plant in PM2.5 Pollution in Taiwan

Taichung Power Plant (TPP) is Taiwan’s largest coal-fired power plant and is considered a major source of air pollution. During periods of deteriorating air quality, it is often required to reduce the load to reduce emissions. However, frequent power load shedding not only requires cost but also requires safety considerations. Therefore, it is necessary to explore the role that thermal power plant emissions play in air pollution in Taiwan. This study employed the Community Multiscale Air Quality modeling system with the brute-force method to analyze the PM2.5 concentration contributed by TPP. The results showed that among the various air basins in Taiwan, the Yun-Chi-Nan air basin (YCNAB), located to the south of TPP, was most severely affected by TPP’s emissions, with an annual average affected concentration of 1.0 µg m−3 (3.3%). However, when serious PM2.5 pollution events (daily concentration > 70 µg/m3) occurred due to low wind speeds, the Central Taiwan air basin (CTAB), where TPP is located, became the area most severely affected by TPP’s emissions. The low wind speed was caused by the interaction between the easterly wind field around Taiwan and Taiwan’s north–south mountain ranges. When this happens, TPP’s emissions would have a greater impact on the PM2.5 concentration at nearby stations in the CTAB and YCNAB, up to about 11%. Overall, on pollution days caused by low wind speeds, the largest TPP load reduction (40%) still had a certain effect as an emergency measure to improve the high PM2.5 pollution in central and southern Taiwan.

ENVIRONMENTAL SAFETY OF ATMOSPHERIC AIR IN THE ZONE OF INFLUENCE OF THERMAL POWER PLANTS WHILE USING SUNFLOWER WASTES

Air pollution is a significant and escalating global issue, posing a major threat to public health. Each year, it directly contributes to 6.5 million premature deaths, primarily due to cardiovascular and respiratory diseases resulting from exposure to air pollutants, notably fine particulate matter (PM). Beyond its well-documented health effects, recent evidence from epidemiological studies and controlled animal research underscore its detrimental impact on cognitive function and brain health. It's worth noting that residing in heavily polluted areas is linked to increased cognitive impairment and a heightened risk of neurodegenerative conditions. This association is particularly strong with pollutants stemming from energy and transportation, such as PM and nitrogen oxides (NOx). The intricate nature of PM pollutants, particularly ultrafine particles (UFP) with a diameter of less than 100 nm, enables them to infiltrate the human body, bypassing various protective mechanisms. Given this context, investigations into the influence of solid-fuel power plants, recognized by the European Environment Agency as major contributors to atmospheric air pollution, are of utmost importance. Existing regulatory and methodological frameworks do not adequately address contemporary realities and requirements, especially concerning the assessment and control of the environmental impact of thermal power plants using agricultural waste as fuel. This study aims to provide scientific and theoretical support for additional aspects related to the emissions of thermal power plants and their effects on both humans and the environment. This research holds particular significance when evaluating the placement of such facilities near populated areas and when making informed decisions regarding energy production technologies from renewable sources.

Vanadium in modern sediments of urban lakes in the North of Russia: natural and anthropogenic sources

Studies have found that vanadium tends to accumulate in the sediments of lakes located in urban areas where fuel oil thermal power plants or boiler houses are present. The highest concentration of vanadium, amounting to 4785 mg/kg, was found in a lake situated less than a kilometer away from a thermal power plant. In contrast, pristine lakes typically have vanadium levels that are consistent with or below the background levels. In certain regions of Karelia, the elevated concentration of vanadium in lake sediments can be attributed to the presence of uranium‑vanadium ores. In urban sediments, vanadium is closely associated with nickel, which can also be released into the environment through the emissions of thermal power plants and boiler houses. It has been observed that vanadium in lakes primarily exists in the solid insoluble fraction, possibly bonded with natural minerals.

Techno-Economic Analysis of a Hybrid System with Carbon Capture for Simultaneous Power Generation and Coal-to-Hydrogen Conversion

Under the growing pressure of decarbonization across industrial sectors, power plants face great challenges in reducing carbon emissions. To improve energy efficiency and reduce the carbon emissions of thermal power plants, a hybrid system with carbon capture for simultaneous power generation and coal-to-hydrogen is proposed, which features comprehensive consideration of the energy demands of power plants and coal-to-hydrogen units. In the proposed system, the reduction of energy demand is realized by heat exchanger network synthesis (HENs) of the internal streams, and a carbon capture unit is then integrated for further reduction of carbon emissions. The techno-economic feasibility of the integrated system is analyzed and discussed by using energy consumption, economics, and emission reduction as major performance indexes. The results show that energy integration saves 108.2 MW of heat, while nearly 90% of carbon emissions are reduced for the system. When comparing the total energy consumption of the subsystems and a stand-alone carbon capture unit, the consumption for cooling and heating utilities in the integrated system is reduced by 8.81 and 9.11%, respectively. In addition, the total overnight cost and the annual operation cost using the proposed integrated system are reduced by 8.51 and 22.69%, respectively, and the cost of hydrogen production decreases by 5.99%. The economics of the integrated system is significantly affected by the market prices of coal and hydrogen. The integrated system has significant advantages in reducing energy consumption and carbon emissions with higher economic performance, which can provide guidance for the low-carbon transition of coal-fired power plants.

Optimization method of wind power consumption based on thermal storage tanks against the background of stepped carbon trading

In the context of Chinese efforts to achieve the goal of “carbon peaking and carbon neutrality” for the “Three North” area heating season, thermal power units, due to their unique operation mode of “fixing electricity by heat” and the resulting problem of insufficient wind power consumption by the night system, were proposed as an optimization method for wind power consumption based on thermal storage tanks in the context of stepped carbon trading. The optimization method is applied to thermal power plants and considers the constraints of cogeneration unit thermoelectric coupling, electrical power balance, and thermal power balance. Taking the lowest total cost of thermal power plants as the objective function, the Cplex solver in Matlab is used to solve the objective function. The wind power consumption by the system, the CO2 emissions of thermal power plants, and the economy of the system are analyzed in different scenarios. The calculation example results show that the model proposed in this article not only improves the wind power consumption rate of the system and reduces the CO2 emission of the thermal power plant but also improves the economy.

The pollen as bioindicator of the genotoxicity of environment

In recent years the male gametes of plants are used for biotesting in ecotoxicology. High proportion of sterile pollen is the indicator of environmental pollution and the presence of mutagens, which cause genetic disturbances. The viability of pollen of Gorodkov’s rowan (Sorbus gorodkovii Pojark) and Scots pine (Pinus sylvestris L.) in the vicinity of environmentally hazard enterprises of the Arctic cities of the Murmansk region have been studied. The following parameters were considered: the number of fertile and sterile pollen and their percentage ratio, the sterility index, and palynotoxic effect of the pollution. High content of the abortive pollen of S. gorodkovii (55–65%), the sterility index (2.1–2.4) and the palynotoxic effect (38.2–50%) indicates the mutagenicity and genotoxicity of the emissions of the Murmansk thermal power plants, that leads to the formation of sterile male gametes. High level of sterility of P. sylvestris pollen (42.5–50.7%), the index of sterility (1.4–1.7) and the palynotoxic effect (19.1–29.8%) indicates, that emissions of the mining and processing plant "Apatit" containes the mutagenic chemicals that have a genotoxic effect on the pine male gametophyte. The pollen of plants can be used for bioindication of environment as the indicator of the impact of gametopathogenic factors.

Comparison of two air quality models in complex terrain near sea shore

Air pollution is the most important environmental problem in Zonguldak, Turkey due to excessive coal combustion and thermal power plant emissions. The city center is located on a complex terrain near the Black Sea shore. There exist some previous studies about PM10 pollution in the study area, but none of them is related to the spatial distribution of the pollutant. This air quality modeling study aims to fill this gap in the literature. Firstly, PM10 emission inventory has been prepared for point, line, and area sources for the year 2011. For that period, bituminous coal was the principal fuel for domestic heating in houses and generating electricity in thermal power plants, therefore particulate matter (PM10) was the leading air pollutant. Emission inventory calculations revealed that 2710.2 tons of PM10 have been emitted to the atmosphere from all sources in the study area. Then, the air quality modeling has been performed for PM10 by using two air quality models: AERMOD and CALPUFF. According to the modeling results, the PM10 pollution levels may pose a health threat to the inhabitants of Zonguldak. The maximum PM10 concentrations predicted by the CALPUFF model were higher than that of the AERMOD model. The model predicted values plus background concentration were validated against the PM10 measurements by using fractional bias, index of agreement, geometric mean bias, and geometric mean-variance. According to the model performance analysis, CALPUFF showed slightly better performance as compared to AERMOD.

Assessing the impact of coal-fired thermal power plant emissions on surrounding vegetation health using geoinformatics: a case study

Assessing the impact of coal-fired thermal power plant emissions on surrounding vegetation health using geoinformatics: a case study

Applying principal component, health risk assessment, source identification for metallic elements of ambient air total suspended particulates at Taiwan Scientific Park.

This study collected ambient air total suspended particle (TSP) concentrations and dry depositions at Taichung Science Park sampling site. The metallic elements concentrations and dry depositions were analyzed. The possible pollutant sources are discussed in this study. In addition, this study used the principal component analysis method to find metallic element sources and their transportation pathway and distributions at Taichung Science Park (T.S.P). The results indicated that the average highest TSP concentrations and dry deposition fluxes occurred in the autumn and winter seasons. The highest average metallic element concentration and dry deposition was Fe, while the lowest average metallic element concentration and dry deposition was Hg(p). The study results further indicated that the lowest metallic element concentrations and dry depositions all occurred in the summer season. The pollutant parcels originated from the northern Taiwan counties and sea surface in the autumn, winter and spring seasons. Factor 1 was responsible for the local industrial emission results and traffic road dust. The metallic elements Hg(p) yield a value greater than 0.7 in Factor 2 which revealed that ambient air particulate pollutants were generated from Taichung Thermal Power Plant (T.T.P.P.) emissions and were transported from the coastal area of mainland China cities. The mean seasonal concentration differences existed for ambient air particulates, and there were no mean seasonal concentrations differences for all metallic elements. In addition, there were no significant mean concentrations differences for all metallic elements and meteorological factors such as temperature, humidity and wind speed. Therefore, the ambient air metallic element emissions were stable and considered primary emissions sources. The health risk value for metallic element Cr was higher than that for the acceptable health risk value suggested by the EPA. Metallic element Cr revealed that it was no mean seasonal concentrations differences. Thus, metallic element Cr was considered came from local emission source at this T.S.P. sampling site.

Purification of thermal power plant emissions from carbon dioxide by the liquefaction method as part of a turboexpander unit

The purpose of this work is to estimate the energy costs for the utilization of carbon dioxide generated by thermal power plants operating on various types of fuel by the liquefaction method as part of a turbo-expander installation, as well as a general assessment of the efficiency of the TPP during the utilization of carbon dioxide. The energy costs for the liquefaction of carbon dioxide in the turbo-expander unit from the combustion products of thermal power plants running on coal, natural gas and heating oil differ slightly and amount to about 5 MJ/kg of fuel burned. The practical application of purification of combustion products of thermal power plants from carbon dioxide by the liquefaction method as part of a turboexpander installation is possible as part of combined-cycle power plants with a simultaneous reduction in electrical efficiency by more than 10 % to a level of less than 50 %.

A 2050 perspective on the role for carbon capture and storage in the European power system and industry sector

Carbon Capture and Storage (CCS) might be a central technology to reach the decarbonisation goals of the European energy system. However, CCS deployment faces multiple economic, technological, and infrastructure challenges. Related literature tends to only focus on certain aspects of the CCS technology or to be limited to a particular sector perspective. In contrast, this paper presents a holistic modelling framework to analyse the long-term perspectives of CCS in Europe by extending the typical analysis from the electricity sector to the industry sector, and by including the CO2 infrastructure level with CO2 pipelines and storage. To this end, we use state-of-the-art models of the electricity sector (generation investment and electricity grid models), the industry sector, as well as the CO2 infrastructure sector. This unique modelling framework analyses the feasibility and costs of CCS deployment in the European Union towards 2050 in three scenarios with the same ambitious climate policy target (~85% CO2 emissions reduction). The main insights on the deployment of CCS in Europe hinges on two factors: i) the development of low-cost power generation technologies with carbon capture (coal and/or gas-fired), and ii) a sufficiently high CO2 price to compensate for the costs of deploying the CO2 transport infrastructure. Once CO2 transport infrastructure is available, CCS will be a preferred mitigation option for the industry sector emissions. The joint use of CO2 infrastructure by the electricity and the industry sector allows for economies of scale and economies of density. In the long term, CCS cannot achieve the 100% decarbonisation target of the energy sector because the technology can only capture 80–90% of the CO2 emissions of thermal power plants. Moreover, the advantages of CCS in terms of energy system costs compared to a system without CCS is rather small, in the range of 2%. It crucially depends on the costs of renewables and the costs of their integration in the electricity grid.

Validation of Point Source Models for Determining Industrial Pollution and Integrating with IOT for vulnerability management

Awareness in Environmental pollution which was restricted to water and wastewater pollution has now been extended to air pollution. In Indian Scenario, the popularity of air pollution is gaining momentum day by day and all metro cities are facing this problem due to increase in traffic and industries located in the vicinity. The major contribution to air pollution is from traffic though there are other sources like smoke from factories and burning of any material. Monitoring stations are not provided in many places as it is a costly investment. Though there are very few monitoring stations in metro cities, the other areas still do not have any means to monitor the quality of air we breathe in. This work deals with validating point source models to predict the pollution due to thermal power plant emissions in Ennore, Chennai. The details of wind speed, wind direction, temperature and humidity play a major role in dispersing the air pollutants. Particulate air pollutant PM2.5, PM10 and SO2 were monitored and the variation of air pollutants during summer and winter were studied. The influence of meteorological parameters in the concentration of these pollutants were analysed by this study. AERMOD software was used to model the data and further predictions with the help of advanced technology are discussed in this paper. Deployment of a system using advanced sensors and systems has enabled us to assess the air quality by integrating IOT with sensors which could facilitate continuous monitoring of the pollutants.

Optimization Economic and Emissions of Hydro and Thermal Power Plants in 150 kV Systems Using the Dragonfly Algorithm

Electricity is one of the energies required by daily living since the greater demand for electricity increases greenhouse emissions that create emission gases resulting in global climate change. The main portion of the output cost is fuel's cost to manufacture electrical energy in thermal turbines. The use of electrical energy is currently rising increasingly following the increasing population. The research aims to optimize hydro generation to minimize thermal generation expense and address economic problems and pollution from shipping. With 2016b using Matlab applications and the lambda iteration process, the analysis method uses the Dragonfly Algorithm method. The analysis found that the average cost of fuel consumption provided by the Dragonfly Algorithm method was IDR 151,164,418 per day with an emission of 917.40 tons per day, based on the simulation results the Dragonfly Algorithm in testing by considering the emission of 5 practical steps. Meanwhile, with the emission of 918,044 tonnes per day, the average cost of fuel consumption produced by the Lambda Iteration method is IDR 151,202,209 per day. Test results can enhance the fuel consumption cost of IDR 37,791 and emissions of 0.641 tons with the Dragonfly Algorithm process.

MODEL OF OPTIMIZATION OF SOCIO-ECOLOGICAL CONDITIONS OF URBANIZED TERRITORIES

. Optimization of the socio-ecological conditions of modern urbanized territories is the most important task of ensuring sustainable urban development. For a comprehensive study of the socio-environmental conditions of the territory of Central Russia, the data of the Federal Information Fund for Socio-Hygienic Monitoring, conducted on the basis of the Federal Center for Hygiene and Epidemiology of Rospotrebnadzor, was analyzed. The analysis of the obtained data shows the need to create a special system for optimizing socio-environmental conditions, which will be based on socio-environmental monitoring based on geoinformation technologies. This monitoring should be a multifunctional subsystem that interacts with other subsystems of the unified state environmental monitoring system. The main objective of the measures aimed at optimizing the socio-ecological conditions of the cities of Central Russia is to minimize the content of pollutants in the atmosphere (as the main natural environment that forms environmental risk zones) – derivatives of the technological pressure of the city. To achieve this goal, it is necessary to implement 3 main tasks on the territory of large cities of Central Russia: 1. To modernize the transport networks of cities with an increase in their capacity, the quality of the road surface, the average speed of vehicles. 2. To minimize atmospheric emissions of thermal power plants and a number of other industrial facilities. 3. To carry out measures for greening the urban space.

Development of 2015 Vietnam emission inventory for power generation units

The 2010 and 2015 Emission Inventories (EIs) for Vietnam Thermal Power Plants (TPP) were concurrently developed using the bottom-up approach. Local activity data, emission factors, and pollution control efficiencies were applied to estimate the annual emissions of individual power plants. As the EIs consider all emission control activities with relevant unit upgrades, the estimated SO2, NOx and PM species were found to be lower than most of the reported EIs by 20–70%. An overestimation (i.e., 3.8 times) of SO2 has been observed in Emission Database for Global Atmospheric Research (EDGAR) EI, which can possibly be attributed to the assumption of no air pollution controls in their inventory. Overall, the newly developed EIs indicate that the annual emissions of coal-fired TPPs were highest among the various types of TPPs, and the largest uncertainty occurred in NOx with ranges between −23% and +31%. In terms of regional distribution, the most significant emission sources of CO2, N2O, SO2, NOx, PM10, PM2.5, BC, and OC were from the Red River Delta region resulted from coal-fired TPPs, while the Southeast region had the largest sources of CO, NMVOC, and CH4 caused by gas-fired TPPs. The study reveals that from 2010 to 2015, the growths of NOx, CO, NMVOC, PM10, PM2.5, BC, OC, CO2, CH4, and N2O emissions were 51%, 39%, 41%, 109%, 88%, 9%, 107%, 58%, 33%, and 119%, respectively, while ~19% reduction in SO2 was found resulted from the decommission of oil-fired TPPs.

Road dust trace elements contamination, sources, dispersed composition, and human health risk in Chelyabinsk, Russia

There are many sources of urban road dust, such as soil dispersal, emissions of industrial enterprises and thermal power plants, road traffic-related processes. Chelyabinsk was selected as a typical Russian industrial city. This work was the first pollution study of road dust in Chelyabinsk. We examined 125 road dust samples were on the content toxic trace elements (As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Sr, and Zn). The concentrations of trace elements in road dust were determined using ICP-MS. Results showed that the metal concentrations in dust were higher than the background value of local soil. The distribution curves of dust were asymmetric, had have two peaks, and showed significant unimodal distribution. The higher share of particles was in the range from 30 … 40 to 250 … 300 μm. The thoracic fraction volume (%) and concentrations of trace elements were higher near metallurgical plants. Cadmium, Сu, Mn, Ni, Sr, Pb and Zn were originated from industry and transport; electrometallurgical plant was source of Cr; Al, Co, and Fe derived from local soils and pavement erosion; As, Hg and Sb were the tracers of coal-fired power stations emission. Ingestion was a major exposure way of toxic elements in the dust. The results suggested that there was no significant potential health risk to both children and adults from exposure to any elements in road dust. The cancer risk for adults and children from exposure to As, Cd, Cr, and Pb was found to be at the acceptable or tolerable level.The study deals with the contamination of potentially toxic trace elements (As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Sb, Sr and Zn) in road dust collected from Chelyabinsk urban area.

Air mass physiochemical characteristics over New Delhi: impacts on aerosol hygroscopicity and cloud condensation nuclei (CCN) formation

Abstract. Delhi is a megacity subject to high local anthropogenic emissions and long-range transport of pollutants. This work presents for the first time time-resolved estimates of hygroscopicity parameter (κ) and cloud condensation nuclei (CCN), spanning for more than a year, derived from chemical composition and size distribution data. As a part of the Delhi Aerosol Supersite (DAS) campaign, the characterization of aerosol composition and size distribution was conducted from January 2017 to March 2018. Air masses originating from the Arabian Sea (AS), Bay of Bengal (BB), and southern Asia (SA) exhibited distinct characteristics of time-resolved sub-micron non-refractory PM1 (NRPM1) species, size distributions, and CCN number concentrations. The SA air mass had the highest NRPM1 loading with high chloride and organics, followed by the BB air mass, which was more contaminated than AS, with a higher organic fraction and nitrate. The primary sources were identified as biomass-burning, thermal power plant emissions, industrial emissions, and vehicular emissions. The average hygroscopicity parameter (κ), calculated by the mixing rule, was approximately 0.3 (varying between 0.13 and 0.77) for all the air masses (0.32±0.06 for AS, 0.31±0.06 for BB, and 0.32±0.10 for SA). The diurnal variations in κ were impacted by the chemical properties and thus source activities. The total, Aitken, and accumulation mode number concentrations were higher for SA, followed by BB and AS. The mean values of estimated CCN number concentration (NCCN; 3669–28926 cm−3) and the activated fraction (af; 0.19–0.87), for supersaturations varying from 0.1 % to 0.8 %, also showed the same trend, implying that these were highest in SA, followed by those in BB and then those in AS. The size turned out to be more important than chemical composition directly, and the NCCN was governed by either the Aitken or accumulation modes, depending upon the supersaturation (SS) and critical diameter (Dc). af was governed mainly by the geometric mean diameter (GMD), and such a high af (0.71±0.14 for the most dominant sub-branch of the SA air mass – R1 – at 0.4 % SS) has not been seen anywhere in the world for a continental site. The high af was a consequence of very low Dc (25–130 nm, for SS ranging from 0.1 % to 0.8 %) observed for Delhi. Indirectly, the chemical properties also impacted CCN and af by impacting the diurnal patterns of Aitken and accumulation modes, κ and Dc. The high-hygroscopic nature of aerosols, high NCCN, and high af can severely impact the precipitation patterns of the Indian monsoon in Delhi, impact the radiation budget, and have indirect effects and need to be investigated to quantify this impact.

Calculation of standards for permissible environmental impact for boilers with known technical characteristics

Emission of thermal power stations and boilers is regulated in accordance with the unified national regulatory requirements, taking into account the specifics of energy production, its life-sustaining function and is aimed at ensuring that air pollution is prevented as much as possible. The purpose of the regulation of emissions of thermal power plants is to limit its adverse impact on the air basin by developing, for the entire thermal power plant and each source of emissions on it, the maximum allowable emissions – control (in grams per second) and per annum (in tons per year), ensuring sanitary hygienic standards. Sanitary standards include the maximum permissible concentration, which reflects the level of components in the air that is safe for humans. In practice, several substances are simultaneously present in the air, the presence of which causes multicomponent air pollution. The atmospheric pollution index, which is calculated for a group of substances, is often used as a complex indicator of the degree of air pollution. Currently, mostly applied methods of component-wise assessment of atmospheric air quality are used in practice. When calculating atmospheric pollution by boiler houses, the total volumes of fuel combustion products are determined experimentally or by calculation. This article provides empirical formulas for calculating the above standards – the volume of flue gases, the maximum one-time emissions of ash, sulfur oxides, carbon and nitrogen for various boilers with known technical characteristics. Also, using the above formulas, a comparative analysis of the level of air pollution depending on the quality of various types of fuel burned in various types ofboilers.

Seasonal Variations of Heavy Metals in the Soil Around a Coal-Fired Thermal Power Plant, South-West Coast of India.

This study focuses on seasonal variations of heavy metals in the soil around a coal fired thermal power plant in Udupi district, which is a densely populated town in the tropical southwest coast of India. This study, pertaining to 48 soil samples, collected during the pre-monsoon, early-monsoon, monsoon and post-monsoon seasons for oneyear, reveals that the chemistry of collected soil samples is influenced by non-pedogenic (anthropogenic) sources such as fly-ash deposition from the thermal power plant and vehicular emissions. This was concluded based on grouping of similar behaved elements through correlation-regression analysis. The distance-wise distribution of heavy metals and backward wind-trajectory analysis suggests that pre-monsoon and post-monsoonal samples are more influenced by anthropogenic activities compared to rest of the seasons. This is supported by high concentration of Zn in pre-monsoon (25.21mg/kg) and post-monsoon (21.32mg/kg) seasons compared to early-monsoon (17.05mg/kg) and monsoon (8.60mg/kg) seasons.