Analysis of urban heat island effect in Visakhapatnam,India, using multi-temporal satellite imagery: causes and possible remedies

The thermal data sets of Landsat for the years 2014 and 2019 are used to assess the transients of land surface temperature (LST) in Visakhapatnam, India. The variation in estimated temperature fields is compared with the land use pattern to validate temperature with reference to land use land cover (LULC). During the considered period, the built-up area in the study region increased by 63%. The aerial extent of water bodies has come down by 12.5%, and there is a significant drop in vegetation cover. The LST of the regions with the densely built-up area is high compared to the other types of land use. A mean rise of 4.8 °C in the LST has been noticed over the study area during this period. Few monitoring points representing rural areas within the proximity of the study region have been established, and the LST is monitored explicitly. As a result, it has been observed that the temperature in rural areas is relatively lower than the city region, which confirms the urban heat island effect. A micro-level study has been conducted by dividing the study area into four zones as per administrative boundaries. Statistical analysis using the zonal attributes affirms a positive correlation of 0.55 between LST and the built-up area. In contrast, a negative correlation of 0.52 between LST and vegetation cover is observed. The LULC results are validated using Google Earth Images captured at a finer resolution. Being selected as one of the cities under the smart city mission by the Urban Development Ministry of Govt. of India, it is expected that the land use pattern in Visakhapatnam will change drastically in the coming years. The findings of this study foster the relationship between LST and LULC, and the conclusions thus drawn would help planners for the sustainable development of Visakhapatnam.

     

Negative effect of litter of invasive weed Lantana camara on structure and composition of vegetation in the lower Siwalik Hills,northern India

Lantana camara, an aromatic shrub, native to tropical America, was introduced into India for ornamental hedging, but later escaped and became a serious invasive weed. This study assessed the quantitative and qualitative status of plant community richness and diversity in areas invaded by L. camara in the Siwalik Hills (Himachal Pradesh, India), and explored allelopathy as a possible mechanism of interference. We measured species diversity, richness and evenness of the vegetation in areas invaded and uninvaded by L. camara. Allelopathic effects of L. camara rhizosphere soil and litter were assessed against two native plants—Achyranthes aspera (a herb) and Albizia lebbeck (a tree). Density, biomass and indices of diversity, richness and evenness were reduced by L. camara, indicating a significant alteration in composition and structure of native communities. Seedling growth of the test species was reduced in L. camara rhizosphere- and litter-amended soil. The inhibitory effect was ameliorated by the addition of activated charcoal, indicating the presence of organic inhibitors (quantified as phenolics) in the soil. Lantana invasion greatly reduces the density and diversity of the vegetation in the invaded area, and chemical interference of its litter plays an important role in invasion.     

Breakthrough Curves Characterization and Identification of an Unknown Pollution Source in Groundwater System Using an Artificial Neural Network (ANN)

Contamination of groundwater constrains its uses and poses a serious threat to the environment. Once groundwater is contaminated, the cleanup may be difficult and expensive. Identification of unknown pollution sources is the first step toward adopting any remediation strategy. The proposed methodology exploits the capability of a universal function approximation by a feed-forward multilayer artificial neural network (ANN) to identify the sources in terms of its location, magnitudes, and duration of activity. The back-propagation algorithm is utilized for training the ANN to identify the source characteristics based on simulated concentration data at specified observation locations in the aquifer. Uniform random generation and the Latin hypercube sampling method of random generation are used to generate temporal varying source fluxes. These source fluxes are used in groundwater flow and the transport simulation model to generate necessary data for the ANN model-building processes. Breakthrough curves obtained for the specified pollution scenario are characterized by different methods. The characterized breakthrough curves parameters serve as inputs to ANN model. Unknown pollution source characteristics are outputs for ANN model. Experimentation is also performed with different number of training and testing patterns. In addition, the effects of measurement errors in concentration measurements values are used to show the robustness of ANN based methodology for source identification in case of erroneous data.     

Autoregressive models in environmental forecasting time series: a theoretical and application review

Environmental Science and Pollution Research - Though globalization, industrialization, and urbanization have escalated the economic growth of nations, these activities have played foul on the...     

Experimental investigation of different-shaped microwave-heated potatoes: thermal and quality characteristics analysis for food preservation

Environmental Science and Pollution Research - Food materials are consumed for nutritional purposes in the form of fruits, vegetables, plants, and meat. These contain proteins, carbohydrates, and...     

Statistical inferences from measured data on concentrations of naturally occurring radon,thoron, and decay products in Kumaun Himalayan belt

Environmental Science and Pollution Research - Regional averages of radon, thoron, and associated decay product concentration are reported to be higher than their respective global averages in...     

Extraction of earthworm from soil by different sampling methods: a review

Earthworms are so closely incorporated into the soil structure that they are not calculated easily from the soil. Due to this property, their extraction from soil is tedious and time-consuming. Different methods have been used for their extraction from the soil, and efficiency of each method is affected by physical properties, viz., temperature and moisture of the soil. This study explored the advantage and disadvantage of different sampling methods for the extraction of earthworms such as hand sorting, octet method, formalin method, mustard extraction method, allyl isothiocyanate (AITC), and onion extraction method. Extraction efficiency of formalin is 20–60 times more as compared to hand sorting, but hand sorting gives satisfactory results for earthworms of more than 0.2 g live weight, and cocoons can also be recovered by this method. Octet method is effective in extracting anecic species and could easily be applied to site where chemical extraction is not a viable option. Extraction by mustard and AITC is simple, low cost, and more efficient for the extraction of deep-burrowing anecic species. The onion extraction solution is low cost and nontoxic which can be used as alternative to formalin. Like mustard, the onion solution is also inexpensive and not harmful to the earthworms and environment.     

Higher Pollution Episode Detection Using Image Classification Techniques

Image classification techniques have been applied to detect higher pollution episodes in modelled air pollution data. These techniques are widely used in video processing to find patterns in videos. An attempt for the first time has been made to apply these techniques by considering air pollution as continuous video frames as the spatio-temporal changes in the pollution are linked to its previous state of the atmosphere. The applicability of these techniques has been tested over Northern Italy to detect ozone pollution episodes in year 2004 using model simulated concentrations. The methods tested in this paper are pixel, block-based, histogram, pertinent pixel and twin-comparison method. While these techniques have some kind of merits and demerits, a modified pertinent pixel comparison algorithm has been proposed to detect pollution episodes. The proposed method has been validated to detect PM10 episodes over Milan metropolitan area during 2 months in 2008 and is able to detect PM10 episodic events as well as non-events. This method provides a single binary index that can be applied by the air quality modellers and decision makers to determine the pollution episode over a given domain.     

Impacts of industrial waste resources on maize (Zea mays L.) growth,yield, nutrients uptake and soil properties

Discharging untreated highly acidic (pH < 4.0), organic and nutrients rich monosodium glutamate wastewater (MW), and highly alkaline (pH > 10.0) paper-mill wastewater (PW) causes environmental pollution. When acidity of MW neutralized (pH 6.5 ± 0.1) with PW and lime (treatments represented as MW + PW and MW + Lime), then MW may be utilized as a potential source of nutrients and organic carbon for sustainable food production. Objectives of this study were to compare the effects of PW and lime neutralized MW and chemical fertilizers on maize (Zea mays L. cv. Snow Jean) plant growth, yield, nutrients uptake, soil organic matter and humic substances. The field experiment was carried out on maize using MW at 6000 L ha^?1. Impacts of the MW application on maize crop and soil properties were evaluated at different stages. At harvest, plant height, and plant N and K uptake were higher in MW treatment. Leaf area index at 60 days after sowing, plant dry matter accumulation at harvest, and kernels ear^?1 and 100-kernel weight were higher in MW + Lime treatment. Kernel N, P, K, Mn, Fe and Zn, and plant Zn uptake were highest in MW + Lime. Plant Fe uptake, and soil organic matter and humic substances were highest in MW + PW. The MW + PW and MW + Lime treatments exhibited comparable results with chemically fertilized treatment. The MW acidity neutralized with lime showed positive impacts on growth, yield and nutrients uptake; nevertheless, when MW pH neutralized with PW has an additional benefit on increase in soil organic matter and humic substances.