Abstract: The 210Pb-based dating method provides absolute ages determination in recent aquatic sediments at centennial scales. It is widely used to support a large variety of environmental studies. However, any empirical data set is compatible with an infinite number of chronologies that need to be constrained by a series of assumptions (models) on the particular sedimentary conditions of the studied environment, and validated with independent chronostratigraphic markers. During five decades, about thirty models have been developed to cope with the wide diversity of natural conditions, a good number of them appearing in recent years, along with new concepts such as model errors, attractors for χ-mapping, or kinetic reactive transport, which have changed common views and practices. This paper aims to present a comprehensive review of this dating method to provide to final users updated tools and a renewed understanding to improve the reliability of their applications. Models are classified in terms of their assumptions on the sedimentary systems, which are better understood from a revisited theory of early compaction and the description of the microcosms of saturated porous media, where composite fluxes of tracers undergo different deposition pathways in terms of physical and kinetic reactive transport. The article reviews empirical evidence on the natural variability in mass flows and initial activity concentrations. Some models allow analytical solutions, while others require numerical techniques. The review is illustrated with examples from real case studies.

Abstract: We propose and validate three linear regression models, using maximum air temperature and retrievals of LST of the MYD21A1D data product (LSTMYD21A1D) as response and predictor variables, for the three major biomes in the São Francisco River Basin as defined by the Instituto Brasileiro de Geografia e Estatística (IBGE) in the Map of Biomes of Brazil (MBB), which is often used to support public policies. A dataset of 94,544 observations of ground-based measurements and retrievals of LST is used to build the models. The efficacy and performance of the models are tested by means of cross-validation and of benchmarking with the linear regression model for the entire basin, regardless the type of biomes. The three proposed linear regression models indicated that LSTMYD21A1D explains well the variations in air Tmax for all the types of biomes in the SFRB (R2: from 0.46 to 0.54). The results of the cross-validation revealed that the three models were equally good at providing estimates of air Tmax across the basin (RMSE < 2.66oC and MAE < 2.14oC), even though they were built with subsets of data sampled in a specific biome. The benchmark test indicated that the models, when applied to their specific biome, provide better estimates of air temperature than the regression model for the entire basin.

Abstract: This study introduces Computational Historical Ecology, a framework that applies GIS mapping, text analysis, and AI tools to historical biodiversity data. The framework not only enhances the utility of archival sources but also highlights the potential of integrating computational techniques with historical and environmental humanities. The study works with the 1845 Bavarian Animal Observation Dataset: a historical survey documenting vertebrate species across 119 forestry districts in pre-industrial Bavaria, which offers invaluable insights into species distribution, habitat changes, and the ecological impact of human activities during the 19th century. By digitising, annotating, and analysing over 5,400 archival records, the research bridges historical ecology and computational methods to reconstruct past biodiversity patterns. Employing a data-centric methodology, the exemplary analyses reveal significant shifts in species presence, driven by land development, deforestation, and evolving agricultural practices. Notable examples include the decline of the Eurasian otter and the extinction of the Eurasian beaver in Bavaria. The interdisciplinary study demonstrates how historical records reflect both environmental transformations and the perspectives of the people who documented these changes. Findings underscore the importance of historical datasets as benchmarks for contemporary assessments and as contributions to ongoing debates in conservation science, restoration ecology, and environmental policy-making. The paper advocates for greater investment in digitisation and interdisciplinary collaboration, recognising the critical role of archival sources in shaping future biodiversity strategies.

Abstract: The Kashmir Valley, characterized by its rich loess-palaeosol sequences (LPS), provides a unique geo-archive for reconstructing Late Quaternary climate and paleoenvironmental dynamics. This study presents an extensive multi-proxy study, integrating high-resolution lithostratigraphy, geochemical analyses, stable isotope analysis of soil organic matter (δ13C-VPDB), and radiocarbon (14C) chronology of a sediment sequence approximately 200 cm thick, to unravel the complex interplay of climatic, pedogenic and environmental processes shaping the region spanning the Pleistocene-Holocene transition. The results establish a precise chronology of the sediment sequence between 13.4 ka and 7.2 ka, covering the transition from the Pleistocene to the Holocene Epoch. The results reveal distinct climatic and environmental conditions during this epoch. The study reveals substantial loess deposition during the cold and dry glacial climate towards the end of the Pleistocene, followed by a shift to a warmer and wetter interglacial climate at the onset of the Holocene Epoch. This climatic shift led to the development of soil units with pronounced fluvial characteristics around 10 ka, eventually transitioning to fluvial deposition. Geochemical indices such as Ca/Ti, Al/Ti, Si/Ti, and K/Ti indicate low weathering intensity prior to 11 ka, followed by a noticeable increase around 11 ka, possibly driven by enhanced precipitation. δ13C values, ranging from –26.2‰ to –22.5‰, suggest C3-dominated vegetation during the Late Pleistocene, indicating wetter climatic conditions. This study provides valuable insights into the intricate interactions between climate, soil development, and vegetation dynamics during the critical Late Pleistocene-Holocene transition in the Kashmir Valley.

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The widely cited claim that 50% of supermarket products contain palm oil appears wrong. Our analysis of ~1,600 products from supermarkets in the Netherlands, United Kingdom, and Australia found palm oil in 7.9% of products, while maize (19%), rapeseed (15%), and soya (14%) were more common. However, up to 40% of products may contain palm oil through unspecified vegetable oils or oleochemicals. While reported declines in palm oil consumption in Europe and Australia, indicate a shift in consumer preferences, these figures correlate with an increased substitution of alternative oils. These alternatives often have higher land requirements than oil palm, raising sustainability concerns. Additionally, incomplete and ambiguous reporting of product composition, particularly for oleochemicals, may obscure the true prevalence of vegetable oils. Regulatory efforts like the EU Deforestation Regulation (EUDR) aim to improve transparency, but challenges remain at the consumption supply chain node where consumers should not only know what vegetable oils are in products, but also the conditions under which those oils were produced. Our findings highlight the need for better food labeling, and impact evaluations, enabling consumers to make informed choices.

Abstract: We modelled the water level variations in a protected playa-lake system (La Ratosa Natural Reserve, S Spain) comprising two adjacent playa-lakes: La Ratosa and Herriza de los Ladrones. For this pourpose, daily water balances were applied to reconstruct the water level. Model results were validated using actual water level monitoring over the past 20 years. We surveyed post-Pliocene geological structures in the endorheic watershed to investigate lake nucleation and to improve the hydrogeological model. Additionally, we investigated the groundwater level evolution in nearby aquifers, which have been profusely affected by groundwater exploitation for domestic and agricultural use. Then, the RCP 4.5 and RCP 8.5 climate change scenarios were applied to forecast the future of this lake system. We found that the playa-lake hydroperiod will shorten, causing the system to shift from seasonal to ephemeral, which appears to be a general trend in this area. However, the impact on La Ratosa-Herriza de los Ladrones system would be likely more severe due to local stressors, such as groundwater withdrawal for urban demand and agriculture, driving to the system to the complete desiccation of for extended periods. These results highlight the sensitivity of these protected ecosystems to changes in the watershed´s water balance and underscore the urgent need to preserve watersheds from any form of water use, other than ecological purposes. This approach aims to support informed decision-making to mitigate adverse impacts on these fragile ecosystems, ensuring their ecological integrity in the context of climate change and increasing water demand for various uses.

Abstract: In the past three decades, the city of Addis Ababa has grown significantly in population, facilities, and infrastructure. The area involved in the recent urbanization is prone to slow natural subsidence phenomena that can be accelerated due to anthropogenic factors such as groundwater overexploitation and loading of unconsolidated soils. The main aim of this study is to identify and monitor the areas most affected by subsidence in a context, such as that of many areas of emerging countries, characterized by the lack of geological and technical data. The increasing availability of SAR data acquired by the Sentinel-1 mission around the world and the refinement of processing techniques that have taken place in recent years, allow one to identify and monitor the critical conditions deriving from the impressive recent expansion of mega cities such as Addis Ababa. In this work, the Sentinel-1 SAR images from 2014 to 2021 were processed through the PS-InSAR technique, which allows us to estimate the deformations of the earth's surface with high precision, especially in urbanized areas. The obtained deformation velocity maps and displace-ment time series have been validated using accurate second-order geodetic control points and compared with the recent urbaniza-tion of the territory. The results demonstrate the presence of areas affected by a vertical rate of displacement of up to 21 mm/year. These areas correspond to sectors that are most predisposed to subsidence phenomena due to the presence of recent alluvial deposits and have suffered greater anthropic pressure through the construction of new buildings and the exploitation of groundwater. Satellite interferometry techniques are confirmed to be a reliable tool for monitoring potentially dangerous geologi-cal processes, and in the case examined in this work, they represent the only way to verify the urbanized areas exposed to the risk of damage with great effectiveness and low cost, providing local authorities with crucial information on the priorities of interven-tion.

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This comprehensive review explores the critical role of microbial adaptation in enhancing food safety by responding to diverse environmental stressors—an essential aspect of microbial ecology with profound implications for biotechnology, environmental management, and public health. We examine the intricate mechanisms underlying microbial adaptation, including genetic modifications such as mutation and horizontal gene transfer, as well as phenotypic plasticity and epigenetic regulation, which enable microorganisms to thrive under adverse conditions. Case studies illustrate microbial resilience in extreme environments, shedding light on their sophisticated adaptive strategies. Additionally, we discuss the practical applications of microbial adaptation in biotechnological domains, including bioremediation, industrial processes, and its emerging contributions to drug development. By addressing future research directions and challenges, this review underscores the necessity of advancing our understanding of microbial-environment interactions to inform innovative strategies for food safety and broader scientific applications.

Abstract:

This review explores advanced sensing technologies and Deep Learning (DL) methodologies for monitoring airborne particulate matter (PM), critical for environmental health assessment. It begins with discussing the significance of PM monitoring and introduces surface plasmon resonance (SPR) as a promising technique in environmental applications, alongside the role of DL neural networks in enhancing these technologies. This review analyzes advancements in airborne PM sensing technologies and the integration of DL methodologies for environmental monitoring. The review emphasizes the importance of PM monitoring for public health, environmental policy, and scientific research. Traditional PM sensing methods, including their principles, advantages, and limitations, are discussed, covering gravimetric techniques, continuous monitoring, optical and electrical methods, and microscopy. The integration of DL with PM sensing offers potential for enhancing monitoring accuracy, efficiency, and data interpretation. DL techniques such as convolutional neural networks (CNNs), autoencoders, recurrent neural networks (RNNs), and their variants, are examined for applications like PM estimation from satellite data, air quality prediction, and sensor calibration. The review highlights data acquisition and quality challenges in developing effective DL models for air quality monitoring. Techniques for handling large and noisy datasets are explored, emphasizing the importance of data quality for model performance, generalizability, and interpretability. The emergence of low-cost sensor technologies and hybrid systems for PM monitoring is discussed, acknowledging their promise while recognizing the need for addressing data quality, standardization, and integration issues. The review identifies areas for future research, including the development of robust DL models, advanced data fusion techniques, applications of deep reinforcement learning, and considerations of ethical implications.

Abstract: Uganda, just like its counterparts around the globe, is transforming its land tenure systems, from communal systems to private individual ownership systems. However, through the establishment of privatized land rights, several criticisms and collisions have continuously marred the government's well-intentioned vision. They claim that this will negatively impact vulnerable groups, such as women, the disabled, and children. In Uganda, while structural transformation occurred in the economy at least thirty years ago, followed by the enactment of the land policy, the issue of rights through titling of individual ownership is not fully implemented to even 50% in the rural areas. This tenure security and ownership empowerment continues to bleed confusion and reportedly leads to the weakening of traditional communal land tenure systems and erosion of land rights, thus hampering sustainable agricultural production and investment. This paper, therefore, examines rural land rights, markets, and land structural transformation in Uganda, with a specific focus on the rural areas. In this work, several papers are reviewed to get facts about existing land rights, land market structure, performance, and challenges associated with them. Review analysis reveals three main issues: there's a lack of awareness of the new land policies and their implementation, land tenure security is not yet guaranteed, and therefore the vulnerable groups are not fully secure, and land markets, though not yet efficient, are increasing exponentially in many areas. In conclusion, this paper recommends the sensitization of the public, especially the rural landowners and institutions, continuous incentivization of formalization and acquisition of land documents, and finally the need to harmonize with different institutions on the implementation of existing land laws and policies.

Abstract: Leaf Area Index (LAI) is one of the key parameters for characterizing leaf density, vegetation growth status, and canopy structure. Rapid, objective, and accurate acquisition of forest LAI is of great significance for studying forest ecosystems and forestry production. This study focuses on the core issue of accurately segmenting leaf elements from background elements in hemispherical photography used for forest LAI measurement, with a particular focus on meeting the real-time requirements of embedded platforms. The differences in grayscale values and frequency characteristics between leaf regions, trunk regions, and sky regions in vegetation canopy images were leveraged to decompose, process, and reconstruct such images using a 9/7 wavelet-based transformation method, achieving efficient and precise segmentation of leaf regions. Through the extraction of canopy gap fraction, rapid LAI measurement was enabled. Comparative experimental results showed that the proposed inversion method exhibited a high correlation with the LAI-2200C measurement results (r=0.847, RMSE=0.431), fully verifying its accuracy across different forest ecological environments. This study provides strong support for the development of portable, high-precision LAI measurement devices and holds practical application value and broad application prospects.

Abstract: Evaluating the impact of pollutants on ecosystems and human health is crucial. To achieve this, a wide range of bioassays, using organisms representative of different trophic levels, are available. However, extrapolating the results of these bioassays to real environmental conditions remains a major challenge. Indeed, how can a toxicity value obtained under controlled laboratory conditions be transposed to an often very different environment? This study specifically addresses this challenge by aiming to develop an algorithm capable of predicting the effect of environmental conditions on the impact of a toxic compound, Pentachlorophenol (PCP). To achieve this, three abiotic factors were considered: pH, temperature, and conductivity. Firstly, the study highlighted the effect of these factors on the biological activity of Escherichia coli. In the absence of the toxicant, pH and temperature are the only factors that significantly influence the activity of this bioindicator. However, when exposed to PCP, the results showed that the sensitivity of the bacteria was affected by pH and conductivity, but not by temperature. From this data, a predictive model was established to assess the intensity of the toxic effect induced by PCP under conditions other than those used in the laboratory test. This model was validated using a dataset of 384 supplementary experiments and demonstrated a strong correlation between the experimental and predicted values (r²≈0.9). Thus, this approach enables the effective prediction of PCP's effects by accounting for environmental variations.

Abstract:

To support coastal practitioners and decision makers manage the complex coastal zone a structured framework was developed to navigate a range of technologies, datasets and data-derived products based on their suitability to monitor the spatial and temporal diversity of coastal processes and morphological indicators. Remote piloted aircraft (RPA) fitted with a LiDAR sensor was used in conjunction with airborne LiDAR and photogrammetry data to undertake foredune change analyses for selected sites in southeastern Australia to validate and demonstrate optimal technology for coastal monitoring. Results were compared with satellite derived coastal change products, including the Digital Earth Australia Coastlines and CoastSat. Foredune volumes from the mid-1900s to 2024 at the highly modified and urbanised Woonona-Bellambi and Warilla Beaches exhibited long-term stability interrupted by large storm events and anthropogenic interventions. Satellite derived data from 1988 onwards showed shoreline regions experiencing the highest rates of seaward extension and landward retreat. The high temporal resolution of this data supports monitoring changes, such as the influence of the El Niño Southern Oscillation on beach rotation. Photogrammetry data with multidecadal temporal coverage provides insights into historical changes. Airborne LiDAR offers three-dimensional data with high spatial resolution to develop accurate terrain models as LiDAR pulses can penetrate foredune vegetation. RPA LiDAR and aerial image data delivered the highest spatial resolution of the beach and foredune region and improves capacity to understand and describe sediment dynamics within a beach or compartment. Rapid deployment capability of RPAs allows for immediate evaluation of impacts from episodic events including storms and management interventions, thereby enhancing hazard mitigation efforts, and improving knowledge of coastal processes. The framework presented in this study emphasises the importance of integrating complimentary monitoring technologies and datasets to improve the temporal and spatial relevance of projections that inform coastal management.

Abstract: Small, forested catchments are prototypes of terrestrial ecosystems and have been studied in several disciplines of environmental sciences since several decades. Time series of water and matter fluxes and nutrient concentrations from these systems exhibit a bewildering diversity of spatiotemporal patterns, indicating the intricate nature of processes acting on a large range of time scales. Nonlinear dynamics is an obvious framework to investigate catchment time series. We analyze selected long-term data from three headwater catchments in the Bramke valley, Harz mountains, Lower Saxony in Germany at common biweekly resolution for the period 1991 to 2023. For every time series, we perform gap filling, detrending and removal of the annual cycle using Singular System Analysis (SSA), and then calculate metrics based on ordinal pattern statistics: the permutation entropy, permutation complexity and Fisher information, as well as their generalized versions (q-entropy and α-entropy). Further, the position of each variable in Tarnopolski diagrams is displayed and compared to reference stochastic processes, like fractional Brownian motion, fractional Gaussian noise, and β noise. Still another way of distinguishing deterministic chaos and structured noise, and quantifying the latter, is provided by the complexity from ordinal pattern positioned slopes (COPPS). We also construct Horizontal Visibility Graphs and estimate the exponent of the decay of the degree distribution. Taken together, the analyses create a characterization of the dynamics of these systems which can be scrutinized for universality, either across variables or between the three geographically very close catchments.

Abstract: Coastal foredunes serve as natural protective barriers, providing defence against storm impacts, erosion, and coastal inundation. In many locations they have undergone significant modifications, including sand mining, re-profiling, urban development, and interventions to enhance recreational amenities. While foredune morphology varies by location, this variation can reveal changes associated with storm events and modifications. This study examines foredune morphodynamics at Woonona-Bellambi Beach in southeastern Australia, using high-resolution three-dimensional LiDAR data to investigate changes across the foredune. The results reveal considerable spatial variability in foredune responses to, and recovery from, large-scale storm events and soft engineering modifications over annual to decadal timescales. Using recently released nearshore wave data, we extracted key storm events over the past decade for this beach which revealed spatially diverse patterns of erosion and recovery of the foredunes. These findings highlight the importance of high-resolution coastal investigations to improve understanding of local-to-regional responses and recovery processes across varying timescales. The insights gained can inform coastal modelling, planning, and management strategies.

Abstract: This study synthesizes 31 years of research (1993–2024) to evaluate agroforestry’s dual role in advancing food security and public health amidst climate change and population growth. Agroforestry—integrating trees, crops, and livestock—enhances agricultural yields, sequesters carbon, and supports biodiversity, while emerging as a critical public health intervention. Analyzing 179 articles from the ISI Web of Science, supplemented by health-focused terms (e.g., "nutrition," "disease resilience"), we document a post-2013 re-search surge. Results reveal agroforestry’s capacity to improve dietary diversity (e.g., +0.231% food security per 1% tree density increase, Singh et al., 2023), reduce malnutrition (e.g., 15–20% lower stunting rates in Kenyan agroforestry households, Quandt et al., 2021), and mitigate climate-related health risks (e.g., 30% reduced heat stress via shade, WHO, 2021). Environmentally, it sequesters 0.5–2 Mg C/ha/year (Jose, 2009), enhancing resili-ence. Yet, longitudinal health impact studies and policy integration remain limited. We propose a transdisciplinary framework uniting agriculture, health, and environmental sectors, prioritizing nutrient-rich agroforestry systems, farmer health education, and cli-mate-health modeling. This positions agroforestry as a scalable solution for sustainable food systems and population health.

Abstract: Accurately understanding the morphological descriptions of plants by ancient people more than 1,000 years ago, and determining the plant species that people described, is of great value in understanding the natural geographic distribution of plant taxa, the var-iation of plant taxa, and climate change. The variation on the plant group and the climate at that time is critical for understanding the change of combination of plant taxa and the climate and the impact of human activity. However, there is limited research in this area. More studies have focused on plant taxa from billions of years ago or money millions of years ago. Research on the plants and flora of this period is limited. And little was known about climates prior to the millennium. In this study, the special text was selected, and the plant names, plants' morphological features were gathered and plant taxonomy were carried out. The study identified 3 species of gymnosperms, namely Pinaceae and Cu-pressaceae, one species of Tamaricaceae monocotyledon, and 19 species of dicotyledons. However, three plant groups could only be identified to the level of genus. In our study, we reconstruct the climate of 1.475 millennia ago through plant textual research and woody plant coexistence analysis in the western section of Henan Province in eastern Asia, in the middle and lower reaches of the Yellow River. The results showed that the mean temperature of the coldest month was around 1.3°C higher than that in modern times, the mean temperature of the warmest month and mean annual temperatures were lower than the corresponding modern values 1.475 millennia ago, implying that tem-peratures in the Luoyang region were slightly lower with a respective mild change at the time, which was supported by other studies of the same period. At the same time, the study concluded that 1.475 millennia ago, the ancient Luoyang region, located in the interior of central East Asia, had high temperatures and rainfall in the summer and low temperatures in the winter, but the mean annual precipitation, the hottest seasonal pre-cipitation, and the coldest seasonal precipitation were all higher than those in the modern Luoyang region. Despite East Asia's predominantly monsoonal climate, the water con-tent of air currents was significantly higher than it is today. This study provides high-resolution plant and climate background information for rebuilding the ecological environment in East Asia.

Abstract:

The assessment of surface water quality of Danube river and Black Sea was performed taking into account the amounts of 9 heavy metals (As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, Zn), nutrients (6 N and P compounds, chlorophyll a), emerging contaminants (pharmaceutics and endocrine disruptors) and heterotrophic bacteria and total coliforms (fecal indicator bacteria) in thirty-two locations from the lower Danube sector (starting with km 375 up to the river mouths), the Danube Delta Biosphere Reserve (three Danube branches – Chilia, Sulina and Sf. Gheorghe) and the Romanian coastal area of the Black Sea. The results for heavy metals, nutrients and bacteria were compared with norms set up in the national legislation for good ecological status for surface water. The concentrations of pharmaceutics and endocrine disruptors from various classes (19 quantified compounds, out of 30 investigated chemicals) were compared with values reported for Danube River water in other studies performed in various river sectors. Correlations between contaminant levels and physicochemical parameters of water samples were studied. This is the first study carried out in the connected system Danube River–Danube Delta–Black Sea for a large palette of toxicants classes and microbial pollutants.

Abstract: The North American Monsoon (NAM) in southern Arizona continues to be a topic of interest to many ecologists studying the triggers and characteristics of plant growth and reproduction in relation to the onset of the monsoon. The purpose of this article is to report interannual variation in the timing of NAM onset found while researching the phenology of Saguaro cactus (Carnegiea gigantea). Using a daily rainfall dataset from 33 stations located in Pima and Pinal Counties, Arizona, from 1990-2022, we analyzed monsoon onset, monsoon precipitation, annual precipitation, and the proportion of annual station precipitation received during the monsoon season. Onset was measured by the first day from 1 June to 30 September with precipitation ≥10 mm counted from the day of the vernal equinox of the year. Generalized Additive Models (GAMs) identified sinusoidal waves with period of 8.6 years and amplitudes of 14-29 days, providing frequency and amplitude estimates for Sinusoidal Regression Models (SRMs). Sinusoidal wave patterns found in the monsoon onset dataset are suggested in monsoon, annual, and proportion of monsoon in station-averaged annual precipitation although in and approximately mirror-image. These unexpected findings may have important implications for forecasters as well as ecologists interested in plant phenology.

Abstract:

Noise is a sound wave that is generally aperiodic in nature, with random and undefined pitch, and which interferes with the quality or detection of other signals. Even so, noise is an unwanted sound that is regarded as an environmental hazard that affects animal and human health. The expansion of urban sprawl, transportation, economic, and development activities is thought to have a significant impact on noise pollution. This research focuses on level of noise in Chattogram Metropolitan Area (CMA) based on both qualitative and quantitative methods. Findings show that, noise pollution level in the study area is exceeded both national and international standard. It will not be an exaggeration to say that noise pollution is endangering city dwellers' quality of life. The noise pollution level is taken several time intervals. According to the study, the noise value is 86.3 dB(A), 87.23 dB(A), 94.07 dB(A) and 84.35 dB(A) at 10 am-12 pm, 2 pm-5 pm, 5 pm-7 pm and 8 pm-10 pm respectively in the industrial area during working day. 78.8 dB(A), 78.03 dB(A), 84.8 dB(A), 76.08 dB(A) at 10 am-12 pm, 2 pm-5 pm, 5 pm-7 pm and 8 pm-10 pm respectively in the industrial area during holiday. 64.0 dB(A), 60.58 dB(A), 62.21 dB(A), 55.95 dB(A) at 10 am-12 pm, 2 pm-5 pm, 5 pm-7 pm and 8 pm-10 pm respectively in the residential area during working day. 58.43 dB(A), 61.71 dB(A), 63.9 dB(A), 57.2 dB(A) at 10 am-12 pm, 2 pm-5 pm, 5 pm-7 pm and 8 pm-10 pm respectively in the residential area during holiday. Noise pollution level in the study area is exceeded both national and international standard. It can be said that city dwellers' quality of life is being endangered by the noise pollution.