Post-monsoon Period Research Articles

Temporal characterization of biogas slurry: a pre-requisite for sustainable nutrigation in crop production

Biogas slurry serves as a useful organic fertilizer due to its substantial nutrient content, and its characterization enables the evaluation of nutrient content and its efficient utilization. This study focuses on the variations in the nutrient content of biogas slurry from different dairy farm systems located near the ICAR-Indian Agricultural Research Institute (IARI) (New Delhi), Daryapur Kalan (New Delhi), and Madanpur (Uttar Pradesh) during the pre-monsoon, monsoon, and post-monsoon seasons. The study reveals significant variations in macronutrient levels, particularly nitrogen (N), which showed variations exceeding 3% and a wider range of almost 6% during the pre-monsoon and post-monsoon periods. Spatial differences between dairy farms also contributed to the variance, with more than 10% differences observed between IARI and Daryapur Kalan and between IARI and Madanpur. Phosphorus (P) remained stable across seasons with spatial variation, while potassium (K) exhibited a reverse trend. Correlation analysis highlighted strong positive associations between N content and phosphorus (0.959), organic carbon (0.954), pH (0.813), and electrical conductivity (0.806). The findings suggest the use of biogas slurry has a potential to reduce the synthetic fertilizer consumption of N, P, and K by approximately 8.78%, 11.01%, and 14.33%, respectively and using them for further for nutrigation.

Seasonal Variations in Condition Factor, Food and Feeding Habit of <i>Labeo bata</i> (hamilton) in Kulia Beel, West Bengal

Labeo bata constitute an important fishery in beels of West Bengal. An attempt was made to study seasonal variations in condition factor as well as food and feeding habit of this fish during pre-monsoon, monsoon and post-monsoon periods (March to November, 2001) in Kulia beel of West Bengal. The relative condition factor varied from 0.907 to 1.076 with higher values during pre-monsoon period. The feeding intensity was found maximum during post-monsoon period. A wide variation was observed in food spectrum of the fish. It fluctuated both season wise as well as with size of the fishes. The details of such variations are discussed.

Biomonitoring of Kulla Beel, a Flood Plain Wet-land, Using Benthic Macro Invertabrates

Kulia beel, a flood plain wetland, located in Nadia District of West Bengal is surrounded by hospital, industries and human settlements. In the present study the ecological assessment through biomonitoring was done by using benthic macroinvertebrates collected from five sites during pre-monsoon, monsoon and postmonsoon periods. Average Shannon-Weaver diversity index (H) was found to vary from 0.953 at S2 during pre-monsoon to 1.683 at S3 during post-monsoon. The evenness index (1) varied from a maximum average value of 0.998 at site S-4 to a minimum average value of 0.614 at site S-1 during pre-monsoon seasons. Both the indices indicate the water body to be moderately polluted.

Future climate change in the Northern Indian Ocean as simulated with a high-resolution regional earth system model

This study examines the future climate change in the South Asia region during 2070–2099 with respect to the historical period (1975–2004) under RCP8.5 scenario using a high-resolution regional earth system model. We found substantial changes in the key climatic parameters over the South Asia region including ocean biological productivity, however, the magnitude of response varies spatially. A substantial increase (> 2.5 °C) in the projected annual-mean sea surface temperature (SST) was found over the Indian Ocean with the highest increase (~ 3.4 °C) locally in the northern part of the Arabian Sea and in the Persian Gulf, SST changes being significant throughout the study area with 95% confidence level. The changes in the sea surface salinity showed strong spatial variability with the highest freshening over northern Bay of Bengal and highest salinity in the Persian Gulf followed by northern Arabian Sea. The amount of annual-mean precipitation will substantially increase over the eastern coast of the Bay of Bengal (up to 1.5–2.0 mm/day) and along the equator in the band 10° S–10° N (0.5–1.5 mm/day), while it will decrease over the western part of the Bay of Bengal and in the northern states of India (− 0.5 to 1.0 mm/day). The most pronounced increase of precipitation rate in the future climate will occur over India (3–5 mm/day) and the eastern coasts of the Bay of Bengal (> 5 mm/day) during the monsoon period, and over the equatorial band (2–3 mm/day) during the post-monsoon period, with all precipitation changes indicated above being significant at 95% confidence level.

Timing of oomycete-specific fungicide application impacts the efficacy against fruit rot disease in arecanut.

Fungicidal application has been the common and prime option to combat fruit rot disease (FRD) of arecanut (Areca catechu L.) under field conditions. However, the existence of virulent pathotypes, rapid spreading ability, and improper time of fungicide application has become a serious challenge. In the present investigation, we assessed the efficacy of oomycete-specific fungicides under two approaches: (i) three fixed timings of fungicidal applications, i.e., pre-, mid-, and post-monsoon periods (EXPT1), and (ii) predefined different fruit stages, i.e., button, marble, and premature stages (EXPT2). Fungicidal efficacy in managing FRD was determined from evaluations of FRD severity, FRD incidence, and cumulative fallen nut rate (CFNR) by employing generalized linear mixed models (GLMMs). In EXPT1, all the tested fungicides reduced FRD disease levels by >65% when applied at pre- or mid-monsoon compared with untreated control, with statistical differences among fungicides and timings of application relative to infection. In EXPT2, the efficacy of fungicides was comparatively reduced when applied at predefined fruit/nut stages, with statistically non-significant differences among tested fungicides and fruit stages. A comprehensive analysis of both experiments recommends that the fungicidal application can be performed before the onset of monsoon for effective management of arecanut FRD. In conclusion, the timing of fungicidal application based on the monsoon period provides better control of FRD of arecanut than an application based on the developmental stages of fruit under field conditions.

Classification of large-scale environments that drive the formation of mesoscale convective systems over southern West Africa

Abstract. Mesoscale convective systems (MCSs) are frequently observed over southern West Africa (SWA) throughout most of the year. These MCS events are the dominant rain-bearing systems, contributing over 50 % of annual rainfall over SWA. However, it has not yet been identified what variations in typical large-scale environments of the seasonal cycle of the West African monsoon may favour MCS occurrence in this region. Here, nine distinct synoptic states are identified and are further associated with being a synoptic-circulation type of either a dry, transition, or monsoon season using self-organizing maps (SOMs) with inputs from reanalysis data. We identified a pronounced annual cycle of MCS numbers with frequency peaks in April and October that can be associated with the start of rainfall during the major rainy season and the maximum rainfall for the minor rainy season across SWA, respectively. Comparing daily MCS frequencies, MCSs are most likely to develop during transition conditions featuring a northward-displaced moisture anomaly (2.8 MCSs per day), which can be linked to strengthened low-level westerlies. Considering that these transition conditions occur predominantly during the pre- and post-monsoon period, these patterns may in some cases be representative of monsoon onset conditions or a delayed monsoon retreat. On the other hand, under monsoon conditions, we observe weakened low-level south-westerlies during MCS days, which reduce moisture content over the Sahel but introduce more moisture over the coast. Finally, we find a majority of MCS-day synoptic states exhibiting positive zonal wind shear anomalies. Seasons with the strongest zonal wind shear anomalies are associated with the strongest low-level temperature anomalies to the north of SWA, highlighting that a warmer Sahel can promote MCS-favourable conditions in SWA. Overall, the SOM-identified synoptic states converge towards high-moisture and high-shear conditions on MCS days in SWA, where the frequency at which these conditions occur depends on the synoptic state.

Estimation of actual evapotranspiration using the simplified-surface energy balance index model on an irrigated agricultural farm

Evapotranspiration (ET) plays a crucial role in the energy and water balance of agricultural ecosystems and is a vital component of the hydrological cycle. Efficient irrigation water management relies on accurate spatiotemporal coverage of crop ET across a farm. Thanks to the availability of multi-temporal high-resolution satellite datasets and remote sensing-based surface energy balance models, near-real-time estimation of ET is now possible. This study utilized Landsat 8/9 data to estimate ET using the simplified surface energy balance index (S-SEBI) model, which was then compared to eddy covariance measurements over a semi-arid agricultural farm in New Delhi, India during the post-monsoon periods of 2021-22 and 2022-23. The S-SEBI model predicted daily ET from Landsat 8/9 data with an average correlation coefficient and RMSE of 0.89 and 0.79 mm/day, respectively. The spatiotemporal map was also used to evaluate the model's performance, and it could accurately differentiate between ET over dryland crops and well-irrigated wheat fields on the farm. Despite underestimating ET (0.51 mm/day) during the initial growing season (Nov-Dec) and overestimating it (0.73 mm/day) during mid-season (Feb-Mar), the S-SEBI model can still be an operational tool for mapping ET with high accuracy and sufficient variation across pixels, making it an ideal option for incorporating into irrigation scheduling.

Bacteriological Characteristics of Meenachil River, Kottayam, Kerala, South India: A Seasonal Study

The Meenachil River is a major river that runs through different taluks, viz. Meenachil, Vaikom and Kottayam of Kerala, India. The Meenachil River's bacteriological characteristics were investigated. Six Meenachil riverine stations were chosen for the investigation. Bacteriological parameters were studied in three different seasons during 2022: monsoon, postmonsoon, and premonsoon. Estimating bacterial production is a critical step in quantitatively understanding the function and contribution of bacteria in material cycling within given aquatic habitats.TCC and FCC values are high during the pre-monsoon season and low during the post-monsoon season.During pre-monsoon, total Coliform number ranged from 230 MPN/100ml to 1100 MPN/100ml, 93 MPN/100ml to 380 MPN/100ml during post-monsoon, and 149 MPN/100ml to 470 MPN/100 ml during monsoon. Escherichia, Citrobacter, Enterobacter, and Klebsilla are examples of coliform bacteria. The highest value of Coliform was 1100 MPN/100ml at station 1 Poonjar during the pre-monsoon period, and the lowest value was 93 MPN/100ml at station 6 Illikkal during the post-monsoon period. Faecal contamination is seen in all the six stations. The bacteria E.coli, Salmonella sp., Pseudomonas sp., Enterobacter aerogenes, Shigelle sp., Vibrio cholerae, Vibrio parahaemolyticus, Proteus sp., Klebsiella sp., have been isolated from various stations, primarily from stations 1, 2, 3, 4, 5, and 6. During pre-monsoon, station 1 in Pooonjar recorded the highest FCC value of 460 MPN/100 ml, while station 6 in Illikkal recorded the lowest value of 20 MPN/100 ml. Although the current situation is not dire or alarming, the river water needs to be closely monitored in order to improve its quality and allow for better and more sustainable management.

Forecasting seasonal TDS using a normalized difference water index in the Ganges River in Bangladesh

The Ganges is one of the most remarkable rivers in Bangladesh. The river contributes to the surface water supply, which is significantly high in the northwest region of Bangladesh. The water quality of this river changed based on many environmental events, and rainfall was one of them. The research focused on finding the mathematical relation between the field observations of water quality parameters and the observed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. This study treated the Total Dissolved Solids (TDS) as one of the crucial parameters in the water quality index, which was monitored and forecasted using multiple linear regression from satellite-derived Normalized Difference Water Index (NDWI) from the Landsat imageries and Electrical Conductivity (EC) from the field observations for the pre-monsoon, monsoon, and post-monsoon periods. The predicted values returned significant correlation coefficient values compared to the field TDS values of 0.64, 0.71, and 0.52 for the three periods, respectively. The regression equations found from this study may be further utilized to predict the TDS values in the future years.

Dengue in Times of Covid-19: A Pre and Post Pandemic Evaluation in East Delhi Population

Background: Dengue is an endemic disease in tropical and sub-tropical regions across the globe with South-east Asian countries showing an increasing prevalence over the years.
 Objective: To observe changes in the disease pattern of Dengue during pre and post pandemic periods.
 Materials and Methods: A retrospective observational study was performed. The laboratory-based study retrieved data for the tests routinely performed for detection of Dengue infection and Covid-19 infection. The positivity rate was calculated for Dengue (2019-21) and for Covid (2020-21). The impact of the Covid-19 pandemic on dengue incidence was studied.
 Observations: It was observed that dengue infection peaked during the monsoon and post-monsoon period. The testing for dengue infection declined by 79.3% when the Covid-19 pandemic struck in 2020. The testing for dengue in 2021 showed an increase of 49.9% when compared to 2019 with a higher positivity rate of 36.4%.
 Conclusion: In the wake of Covid-19 pandemic, as the healthcare system became focused on managing the emergency-like situation and routine diagnostic protocols thus, the control measures for vector borne diseases were disrupted. The surge of dengue cases in 2021 indicates that onset of Covid-19 created a smokescreen which gave rise to increased spread of dengue in the following year. Therefore, it is prudent to incorporate measures to ensure that the control and management of other diseases continues to run seamlessly even during emergence of future epidemics/pandemics.

Mapping of tide-dominated Hooghly estuary water quality parameters using Sentinel-3 OLCI time-series data.

The study explores the spatio-temporal variation of water quality parameters in the Hooghly estuary, which is considered an ecologically-stressed shallow estuary and a major distributary for the Ganges River. The estimated parameters are chlorophyll-a, total suspended matter (TSM), and chromophoric dissolved organic matter (CDOM). The Sentinel-3 OLCI remote sensing imageries were analyzed for the duration of October 2018 to February 2019. We observed that the water quality of the Hooghly estuaries is comparatively low-oxygenated, mesotrophic, and phosphate-limited. Ongoing channel dredging for maintaining shipping channel depth keeps the TSM in the estuary at an elevated level, with the highest amount of TSM observed during March of 2019 (41.59g m-3) at station A, upstream point. Since the pre-monsoon season, TSM data shows a decreasing trend towards the mouth of the estuary. Chl-a concentration is higher during pre-monsoon than monsoon and post-monsoon periods, with the highest value observed in April at 1.09 mg m-3 in station D during the pre-monsoon period. The CDOM concentration was high in the middle section (January-February) and gradually decreased towards the estuary's head and mouth. The highest CDOM was found in February at locations C and D during the pre-monsoon period. Every station shows a significant correlation among CDOM, TSM, and Chl-a measured parameters. Based on our satellite data analysis, it is recommended that SNAP C2RCC be regionally used for TSM, Chl-a, and CDOM for water quality product retrieval and in various algorithms for the Hooghly estuary monitoring.

Trend Analysis of Groundwater Levels in Kalpathypuzha Sub-Basin of Bharathapuzha, Kerala in India

Groundwater is one of the most precious and significant sources of water in the world. The understanding of groundwater level variability and trend is crucial for water resources planning in a region. The present study was conducted in the Kalpathypuzha sub-basin of Bharathapuzha. The variability of ground water levels was analyzed using various descriptive statistics such as mean, standard deviation, coefficient of variation, skewness and kurtosis. The groundwater level trend was estimated using the Mann-Kendall test and Sen’s slope estimator. Twelve observation wells evenly distributed in the blocks of Kuzhalmannam, Palakkad, Malampuzha and Chittur blocks of Palakkad districts in Kerala were selected for the study. The results of variability analysis showed that, the highest mean monthly groundwater level of 139.1 m was found for the well 139 of Chittur block in September and the lowest mean monthly groundwater level of 61.5 m was found for the well 129 of Palakkad block in September. The highest mean annual groundwater level was 138.9 m in the year 2007 for the well 139 of Chittur block and the lowest was 62.1 m in the year 2016 for the well 129 of Palakkad block. The results of trend analysis showed a decreasing pre-monsoon groundwater level trend in three wells viz. well 129 of Palakkad block and wells 133 and 142 of Malampuzha block while decreasing post-monsoon groundwater level trend was observed in well 139 of Chittur block. There was no significant trend in the rest of the wells for both the pre-monsoon and post-monsoon periods.

Assessing Impacts of Mining-Induced Land Use Changes on Groundwater and Surface Water Quality Using Isotopic and Hydrogeochemical Signatures

The current investigation aimed to assess the impact of land use changes on groundwater quality because of the extensive mining activities in the coal mining province of the Mahan River catchment area, which is located in the Surguja district of Chhattisgarh, India. The water quality index (WQI), Collin’s ratio, stable isotope ratios of water molecules (δ18O and δD), and various physicochemical parameters were measured to determine the suitability of water for domestic purposes. Water samples collected from dug wells, tube wells, river water, and mine water were analyzed, and the results revealed that 28% of the samples were classified as excellent and 44%were classified as good during the pre-monsoon period. In the post-monsoon period, 50% of the samples were categorized as good, while 35% were classified as poor, whereas in mining areas, 54% of samples were found to be unsuitable during the pre-monsoon period, and this increased to 77% in the post-monsoon period. Stable isotope analysis was also conducted: samples were plotted to the right of the Local Meteoric Water Line (LMWL) in the isotope bivariate plot, and the observed slopes for all samples were smaller than that of the LMWL. The enrichment of the δ18O ratio and negative d-excess values at certain locations suggest the occurrence of non-equilibrium processes and mixing mechanisms.

Assessment of vegetation variation and its response to ENSO and IOD in the semi-arid ecosystem of Western India

Abstract The variation in the vegetation pattern reflects the change in the regional environment. Normalized Difference Vegetation Index (NDVI) data from 2000 to 2022 for the Upper Bhima sub-basin in Western India has been used to identify the response of vegetation to the El Niño-Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD) events. As a novelty, the present study identifies the ENSO-sensitive and IOD-sensitive vegetation areas within the watershed using vegetation mean to difference anomalies. Monthly NDVI anomalies are used to determine sensitive pixels of vegetation using mean monthly NDVI. Local spatial autocorrelation (LISA) is performed to analyze the pattern of the NDVI anomalies and cluster maps are generated. The results of spatial variation show that NDVI is adversely affected in El Niño years. During La Niña years, the percentage area covered by dense vegetation is more than 80%, which is significantly higher than that of El Niño years in the monsoon and post-monsoon periods. Positive IOD years show significantly more sparse vegetation cover than negative IOD years. The results of LISA analysis show that the rainfall shadow zone in the study area has a cluster of negative sensitive pixels even in the monsoon and post-monsoon period except in negative IOD year.

Evaluation of Disturbance Zonation of Bagmati River System using Benthic Macroinvertebrates in the Kathmandu Valley, Nepal

The existence of Nepal's holy river, Bagmati, which flows through the core of Kathmandu Valley has been menaced by many anthropogenic threats. It is necessary to identify how vulnerable it has been. This research focuses on the evaluation of disturbance zonation to analyze the Bagmati River System’s spatial biological health. Benthic macroinvertebrates (BMIs) were used as biological indicators and were sampled from upstream to downstream using a multi-habitat sampling approach during the post-monsoon period in 2021. The Ganga River System Biotic Score/Average Score per Taxa (GRSBIOS/ASPT) was used to assess river water quality. From the sampling of 21 sites, a total of 5839 individual BMIs from 51 Families and 11 Orders were recorded. Upstream accounted for more than 30% of all the families, making upstream rich in taxonomic preferences, which steadily decreased from midstream to downstream. Facultative taxa were widely distributed in both upstream and midstream, but sensitive taxa were limited to upstream only. There are no signs that facultative and sensitive taxa existed downstream and were fully dominated by pollution-tolerant species. According to classification, the upstream river within Shivapuri Nagarjun National Park of the Bagmati River System was clean and was categorized as Class I, whereas rivers from the boundaries of the protected area to downstream were categorized as Class IV-V with few sites as Class II and Class III, indicating that this stretch of the river was extremely polluted. Water resource managers should utilize the study's findings to assess and restore the water's quality using biological indicators.

Epidemiological analysis of dengue’s one-year laboratory data in a tertiary care center in Western India

Background: Aedes aegypti and Aedes albopictus are the primary effective vectors for the dengue virus in India. The disease is conveyed through the bite of infected mosquitoes of the Aedes species and is the most quickly expanding vector-borne viral disease globally, putting an increasing number of locations at risk. Methods: We looked at the laboratory surveillance data and reported the percentage of dengue cases that were confirmed in the lab by month, location (urban vs. rural), and individual (age vs. gender) factors. Results: The maximum no. of suspected cases as well as found positive were in the monsoon and post-monsoon period from July to November. The dengue suspected cases were significantly more in the adult age group than in the pediatric age group. More cases were seen in urban areas than the rural areas. Conclusions: Serology confirmed positive dengue cases were maximum in the adult group residing in an urban area in the period of monsoon and post-monsoon period from July to November.

A Review on Mango Gummosis Incited by Lasiodiplodia theobromae

Mango gummosis caused by Lasiodiplodia theobromae (Pat.) Griffon & Moube [synonym: Botryodiplodia theobromae] is a serious disease in India especially on popular varieties of mango during monsoon and post-monsoon periods. Severe infection with pathogen causes up to 30- 100 % yield losses in mango. Gummosis infected orchards shows abundant gum secretion from branches, stem and main trunk and also Vascular discoloration. In severe cases infected mango trees may die. The pathogen produces grey-brown to black colonies with dense aerial mycelia on the PDA medium. Pycnidia were separate or aggregated, dark brown, thick or thin-walled. Conidiophores were hyaline, cylindrical to sub-obpyriform, with oblong, straight and hyaline single celled conidia andinitially. Gradually the conidia became dark brown and produced one septum with longitudinal striations. The pathogen has wide host range so difficult to manage the disease at field level. There are sevral Management strategies for mango gummosis like resistant or tolerant varieties, effective fungicides, botanicals and effective biological control agents role in disease management. This review attempts to summarize the Knowledge on mango gummosis, symptomotology, pathogen host range, morphological and cultural characters of Lasiodiplodia and management of the disease.

Ensemble surface soil moisture estimates at farm-scale combining satellite-based optical-thermal-microwave remote sensing observations

Remote sensing presents great potential for soil moisture mapping, although a lack of high-resolution, all-season suitable data and model-based complications hinders continuous mapping at the farm scale. The current study attempts to access optical (Sentinel-2) and microwave (Sentinel-1) based Water Cloud Model (WCM), optical and/or thermal-based Thermal-Optical TRApezoid Model (TOTRAM), and Optical TRApezoid Model (OPTRAM) utilizing Landsat-8 data, and an ensemble of these three models synergistically using microwave, optical and thermal remote sensing data for fourteen dates spanning two post-monsoon periods over a semi-arid irrigated agricultural farm. The ensemble model developed with Gradient Boosting Machine (GBM) offered a superior SSM estimate for the entire crop growth season. The ensemble model had the lowest RMSE (0.053 m3 m−3), followed by OPTRAM (SWIR2) (0.06 m3 m−3), while TOTRAM recorded the highest RMSE (0.092 m3 m−3), even though the model performances varied throughout crop growth cycles. For SSM mapping in the early phases of crop growth, WCM or TOTRAM were found superior, while during the latter growth stages, the performance of OPTRAM was better. In contrast to TOTRAM, which needs local calibration as the land surface temperature is sensitive to atmospheric conditions, the study emphasizes the shortcomings of WCM in terms of calibration requirements for changing vegetation structure utilizing in situ data. OPTRAM is suitable for generating SSM maps in semi-arid environments with a predominance of clear skies throughout the post-monsoon season. It is straightforward, low data, and resource intensive with universal surface reflectance-soil moisture association. The ensemble technique can be recommended for farm-level irrigation mapping over a post-monsoon period.

Bioacoustics, breeding ecology and range of the Kerala warty frog Minervarya cf. keralensis from north of the Palghat gap, central Western Ghats

Minervarya cf. keralensis has been detected for the first time north of the Palghat gap in the central Western Ghats, a range extension of about 85 km. This species calls and breeds in the post-monsoon period (Jan–March) and exhibits axillary amplexus. Male call characteristics, natural history observations, and distributional complexities are described. Currently, the Minervarya nilagirica group that includes M. keralensis, show a complex distribution pattern in peninsular India that is worthy of further phylogeographic study.

Synergistic cancer risk assessment from PM1 bound metals and PAHs in the Indo-Gangetic Region

The atmospheric particulate matter (PM) contains a significant amount of human carcinogens such as metals and Polycyclic Aromatic Hydrocarbons (PAHs). Previous studies have clearly shown that these carcinogens pose serious health issues due to the inhalation of particulate matter. Since the synergistic roles of these carcinogens are rarely considered, these studies frequently underestimate the health risk to humans. The current research aims to bridge this information gap by estimating the synergistic carcinogenic risk assessment owing to PM1 bound metals and PAHs across the densely populated Indo-Gangetic Plain (IGP). The carcinogenic risk assessment was conducted in accordance with the USEPA guidelines on these various PM1 bound components. The Incremental Lifetime Cancer Risk (ILCR) due to heavy metals, such as Lead (Pb) and Chromium (Cr), was found beyond the acceptable limit (> 10−4). The risk due to PM1 bound USEPA PAHs was also significantly higher (> 10−5). This study further estimated the potential toxicity from broad domain of environmental PAHs present in ambient air by considering relevant estimation factors from existing literature. The projected risk from these diverse environmental PAHs was of the order 10−4. Further, source identification of PAHs based on diagnostic isomer ratios revealed that diesel exhaust, biomass burning, and coal combustion are the dominant PAHs sources. Moreover, the exposure to these pollutants is higher in winter and post-monsoon periods. Overall, the synergistic carcinogenic risk found from metals and PAHs was of the order 10−3. In a nutshell, inhalation of PM1 bound heavy metals and PAHs at IGP can result in the development of 1000 cancer cases per million population, which is the highest value compared to other parts of the world. The present study demands immediate policy interventions not only for the reduction of particulate pollution, but also for the reduction of carcinogenic species from the ambient air in order to improve human health.