Pollution Parameters Research Articles

APPLICATION MULTIPLEX PCR FOR EARLY DETECTION ESCHERICHIA COLI CONTAMINATION IN SOME DRINKING WATER RESOURCES IN ABEPURA, PAPUA INDONESIA

Abstract Microbial detection takes a long time to produce positive results, so a quicker detection method was chosen. Multiplex polymerase chain reaction (m-PCR) identified bacterial strains in less than 24 hours, detects E.coli specifically, and is faster than traditional methods. The goal of this study was to use m-PCR to detect early pathogenic E.coli bacteria in several drinking water sources in the Abepura district of Papua Indonesia as a parameter of pollution and water quality. The Chelex100 and microwave combination method was used to extract DNA. The first round of testing was done at four different concentrations: 0.125, 0.250, 0.375, and 0.500 M. The purity of the extracted DNA was good, ranging from 1.80 to 1.94. The optimum primer concentration for multiplexing applications is 0.25 uM for lt primer; 0.125 uM for stx2 and eae primer, with an annealing temperature of 55oC. m-PCR has been shown to quickly detect pathogenic E. coli in water samples. In the PCR process, E.coli DNA template was obtained with high purity (1.80-1.94) and concentration (576.9-4301.6 ng/uL) . Each multiplex set included three primer pairs for the target gene lt-eae-stx2 on ETEC-EPEC and EHEC respectively. The m-PCR process showed excellent results, and this findings can be considered as a reference for water analysis in several drinking sources in Papua Province.

Synthesis, Characterization, and performance test of modified Zeolite-Si/Al nanocomposite from pumice and waste cans using slow pyrolysis process for removal pollutant parameters from hard water

Hard water is one of crucial problems in the world due to its pollutant parameters. Adsorption is a promising method for treating hard water because of its benefits such as low-cost, easy to use, acceptable, and easy to maintenance. In this study, we utilized zeolite functionalized with silicon/aluminum (Ze-Si/Al) as adsorbent materials for hard water treatment. Ten different ratios of Si/Al were added into zeolite by modifying the solid waste source concentration (pumice and cans). The optimum sample was then further tested with different parameters including contact time, dye concentration, and isotherm models. The zeolite-Si/Al adsorbent was characterized by Scanning Electron Microscope (SEM), X-Ray Diffraction (XRD), and X-Ray Fluorescence (XRF). Results of this study have showed that the best functionalized zeolite was that with Si/Al ratio 0.67, which has higher sorption ability. In contact time test, the equilibrium was reached after 300 min. This study also informed that the concentration of dyes will give impact on removal of pollutant parameters. Isotherm model of Ze-Si/Al fitted with Langmuir method. This study also discussed the potential development and future research direction. Thus, this study is a crucial report to develop the information about waste utilization as source of Si/Al to increasing quality of zeolite.

Water quality variation and driving factors quantitatively evaluation of urban lakes during quick socioeconomic development

Rapid urbanisation has caused a significant impact on the ecological environment of urban lakes in the world. To maintain the harmonious development of urban progress and water quality, it is essential to evaluate water quality variation and explore the driving factors quantitatively. A comprehensive evaluation method with cluster analysis and Kriging interpolation was used to explore the spatiotemporal variation in a typical urban lake in China, Chaohu Lake, from 2011 to 2020. The correlation between water quality and socioeconomic factors was evaluated by Pearson correlation analysis. Results indicated that: total phosphorus (TP) and total nitrogen (TN) were the key pollution parameters of Chaohu Lake. The pollution situation was gradually improving, however, and the improvement in chemical oxygen demand (COD) is more evident due to anthropogenic control. The spatial heterogeneity of water quality in Chaohu Lake is remarkable, and the water quality is poor in the west but better in the east. Natural attributes of lakes and external load were the main reasons for the spatial heterogeneity. The western residential areas of Chaohu Lake Basin (CLB) are concentrated, and a large amount of industrial and domestic sewage exacerbates water pollution in the west of tributaries. In contrast, the implementation of water environmental governance policies in recent years has alleviated water pollution. From 2011 to 2020, water quality has improved by 23%–35% in the west and 7%–14% in the east. This study provided a framework for quantitatively assessing water quality variation and its driving forces in urban lakes.

A baseline study on mortality and air pollution in Kabyle village (northern Algeria) under COVID-19

The present work is a preliminary study of mortality data and fine particulate matter (≤ 2.5 µm, PM2.5) concentration in Kabyle village (northern Algeria) under COVID-19. Three epidemiological measures were used to quantify COVID-19-attributable mortality during the years 2019, 2020, 2021 and the first half of 2022, namely monthly death count, crude excess mortality (EM) and P-score (%). In addition, PM2.5 concentration was measured three times minimum in the morning (between 6:00 and 10:00 a.m.) for 2 to 25 days depending on the month, from August to October 2021 and from January to June 2022 to look for a possible correlation between air quality and monthly excess mortality. The P-score, as the most interesting parameter for comparison purposes, was found to range from approximately -67 % (in 2021, for women 65 years and older) to 133 % (in 2021, for men 65 years and older). For those under 65, the P-score is undefined, either because their EM is zero (the case in 2021 for men under 65) or because expected mortality is zero. The daily PM2.5 concentration varied from 0.5 to 150 µg/m3 during the entire observation period. A moderate positive correlation was found between monthly EM and monthly PM2.5 concentration, for women of all ages only (Kendall’s tau (τ) ~ 0.22, p = 0.00). This work could inspire other larger studies, which should include, for example, all the 23 villages of the municipality, considering other air pollution parameters with, in addition, a more consequent recording frequency.

Boundary null controllability of convection-diffusion equations with constraints on the state and application to the identification of boundary pollution parameters

We study a null controllability problem for a convection-diffusion equation with the control contained in Fourier boundary condition to identify M parameters of pollution. The results are achieved by means of an observability inequality derived from new Carleman estimates for the boundary null controllability and the construction of a boundary sentinel to identify the parameters.

Investigation of Soil Pollution with Pollution Parameters (Erzurum-Moryayla)

Soil samples in Moryayla village located 156 km northeast of Erzurum and Cu mineralization area around it were collected randomly. In these samples, 20 samples were taken in order to investigate the metals found and the pollution limits of these metals and the sources that cause this pollution. The geochemical analyzes (Cd, Cr, Cu, Ni, Pb, Zn and Fe) of the collected soil samples were made and evaluated with the pollution parameters. In the calculation of these parameters, enrichment factor (EF); geoaccumulation index (Igeo); contamination factor (CF) and pollution load indices (PLI) were used by using average shale values and crust values. Statistically obtained Cu values were calculated as minimum 25.2 ppm, maximum 79.7 ppm and average 45.2. Among the statistically analyzed elements; A high positive correlation was observed between Cd and Pb and Zn, Cr with Ni and Pb and Zn (p

Тяжёлые металлы в почвах различных функциональных зон урбанизированных территорий: оценка содержания и экологического риска

In order to analyze heavy metal pollution of urbanized soils of the city of Vladimir, the selection and study of soil samples was carried out. Soil samples were analyzed for lead, zinc, copper, nickel, manganese, cobalt and chromium. The obtained indicators were compared with the maximum permissible concentrations and background values. The regularities between the proximity of the studied sites to industrial enterprises and the concentration of heavy metals in the soil are established. The coefficients of accumulation of heavy metals in soils have been calculated and metals that are priority pollutants with the highest accumulation coefficient have been identified. By calculating the total accumulation index of heavy metals, the territory of the city is differentiated by the degree of danger. The calculation of such indicators as: the general pollution index PLI, the indicator of potential environmental risk PERI, the Nemerow pollution index (NPI). It has been established that lead, arsenic and zinc are priority pollutants. The use of various calculated parameters of pollution allowed us to reveal a more detailed picture of the spatial distribution of heavy metals in the soils of urban landscapes under the influence of a strong anthropogenic load. Despite the differences in the calculation of the indices, a high correlation was found between the values of the total pollution index (Zc), the Nemerow pollution index (NPI) and the potential environmental risk index (PERI). The degree of soil contamination of various functional zones according to the indicator of potential environmental risk and the general pollution index PLI increases in the following series: zones of multi-storey buildings < zones of green spaces < zones of transport infrastructure < zones of low-rise buildings < industrial zones.

Research on the carbon emissions traceability inventory and multi-horizon prediction of ship carbon emissions: a case study of Tianjin Port

IntroductionIn recent years, the adverse effects of escalating maritime trade and international shipping– particularly in regard to increased greenhouse gas emissions and their impact on human health– have come to the fore. These issues have thus instigated a surge in pressure to enhance the regulation of shipborne carbon emissions.MethodsThe study utilized the automatic identification system (AIS) data, Lloyd’s register data, and pollutant emission parameters to calculate the carbon emissions from the main engine, auxiliary engine, and boiler of vessels under varying sailing conditions, utilizing the dynamic method of ships. In relation to geographic information and ship trajectory, a comprehensive inventory of ship carbon emissions was developed, revealing pronounced spatiotemporal characteristics. To assure the accuracy of the substantial AIS dataset, procedures including data cleaning, trajectory integration, data fusion, and completion were executed. Such processes are indispensable, given the potential for transmission and storage errors associated with AIS data. To forecast CO2 emissions over diverse time intervals, a temporal fusion transformer model equipped with attention mechanisms was employed.ResultThe paper furnishes a case study on Tianjin Port, wherein a high-resolution carbon emissions inventory was devised based on AIS data acquired from vessels. This inventory was subsequently employed to generate multi-feature predictions of future carbon emissions. Given the optimal parameter configuration, the proposed method attained P50 and P90 values of 0.244 and 0.118 respectively, thereby demonstrating its efficacy.DiscussionRecognizing the sources of ship carbon emissions in this region and forecasting such emissions in the future substantiates that this method accurately portrays the laws of ship carbon emissions. Our study provides a scientific basis for decision-making in port and pollution management, enabling the creation of targeted emission reduction policies for ships.

Association of air pollution and COVID-19 in India.

The COVID-19 pandemic has affected the world, leading to significant morbidity and mortality. Various meteorological parameters are considered essential for the viability and transmission of the virus. Multiple reports from various parts of the world suggest a correlation between the disease spread and air pollution severity. This study was carried out to identify the relationship between meteorological parameters, air pollution, and COVID-19 in New Delhi, one of the worst-affected states in India. We studied air pollution and meteorological parameters in New Delhi, India. We obtained data about COVID-19 occurrence, meteorological parameters, and air pollution indicators from various sources from April 1, 2020, until November 12, 2020. We performed correlational analysis and employed autoregressive distributed lag models to identify the relationship between COVID-19 cases, air pollution and meteorological parameters. We found a significant impact of particulate matter (PM) 2.5, PM10, and meteorological parameters on COVID-19. There was a significant positive correlation between daily COVID-19 cases and COVID-19-related deaths with PM2.5 and PM10 levels. Increasing temperature and wind speed were associated with a reduction in the number of cases, while increasing humidity was associated with increased cases. This study demonstrated a significant association between PM2.5 and PM10 and daily COVID-19 cases and COVID-19-related mortality. This knowledge will likely help us prepare well for the future and implement air pollution control measures for other airborne disease epidemics.

Status Mutu Kualitas Udara Ambien Pada Beberapa Kota Besar di Papua Menggunakan ArcGIS

The increase in population in recent years has affected the utilization of facilities and infrastructure, including the use of vehicles. For the past 10 years, the population in Papua has increased by around 4.13% per year, resulting in the need for daily mobility to increase. The high mobility demand in Papua could affect the increase in pollution, thus affecting the air quality. Exposure to pollutants in ambient air and environmental noise in the long term will have an impact on human health. Therefore, in this study, we analyze the current conditions of air pollution parameters in several major cities in Papua, such as Jayapura, Merauke, Sentani, and Timika. The method used is a survey. Environmental parameters measured were air content of SO2, NO3, PM 10, PM 2.5, HC, O3, CO, dust, Pb, noise, and The Air Pollutant Standard Index (ISPU) value. Observational data obtained were analyzed and displayed using the ArcGIS program. The parameters for determining the location of sampling points are densely packed highway areas, industrial areas, residential areas, and offices. The results of the study indicated that the ambient air quality in all study sites is below the required quality standard. While the results of environmental noise that exceed the highest quality standards located in specifics area on each study site are as follows, Merauke at PLTD Merauke I PT. PLN Persero with 81.24 dB(A), Sentani at Sentani City Square Roads with 70.2 dB (A), Mimika at Perumahan Pemda SP-2 with 65.30 dB(A), and Sentani at Kantor Bupati Jayapura with 64, 54 dB (A). However, the ISPU value for pollutant substances is still in the range of 0-50, which means that the air quality category is very good to carry any outdoor activities, and does not have any negative impact on humans, animals, or plants.Key words: air quality; noice; ISPU; Papua.

Investigation of simultaneous effects of noise barriers on near-road noise and air pollutants

Noise barriers are one of the common solutions to control road traffic noise. Many studies have also shown that noise barriers cause reductions in near-road air pollutant concentrations. In this study, the simultaneous effects of a specific noise barrier application on near-road noise and air pollution at a specific location were investigated. In this context, air pollution, noise, and meteorological parameters were measured simultaneously at two points, road and receptor sides of a 50 m long, 4 m high glass fiber reinforced concrete noise barrier on a highway section. Results indicated that the noise barrier has an average 23 % reduction effect on the NOx concentration in addition to the noise level reduction at the receptor side. Besides, bi-weekly average passive sampler measurement results for BTEX pollutants indicate lower values at the receptor side of the barrier compared to the free field measurement results. In addition to real-time and passive sampler measurements, NOx and noise dispersions were modeled using RLINE and SoundPLAN 8.2 software, respectively. Comparisons of the measurement results with the model results indicated strong correlations. Model-calculated NOx and noise values under the free field conditions are highly compatible with a correlation coefficient (r) of 0.78. Although the noise barrier has a reduction effect on both parameters, it has been observed that their dispersion mechanisms are different. This study showed that noise barriers considerably affect the dispersion of road-sourced air pollutants at the receptor side. Further studies are needed to optimize noise barrier designs with different physical and material properties and application scenarios considering noise and air pollutants together.

Studies on the efficiency of fish scale adsorbents for treatment of fish processing effluent

AbstractPollution of water by organic and inorganic contaminants is a serious environmental issue. The primary emphasis of this present investigation was to reduce wastewater pollution and environmental burden related to fish waste disposal. Prime pollutant parameters such as biological oxygen demand (BOD) and chemical oxygen demand (COD) in fish processing effluent were treated by adsorbents produced from waste fish scales viz., dried fish scale adsorbent and fish scale biochar. A control was used and the entire study was carried out in batch mode to assess the influence of adsorbent dosage levels, contact time, and pH conditions. The experiments revealed that prepared fish scale biochar was as effective as control in achieving a significant (p < 0.05) reduction of BOD (87%) and COD (84%) at 150 min treatment time with 0.24 and 0.48 g dosage level. The optimum pH range was found to be 6–8. The experimental data fitted well with pseudo‐second‐order and Langmuir isotherm models (R2 > 0.911). The influence of intraparticle diffusion in adsorption treatment was tested with Weber–Morris plot. The experiments were done in triplicate and all data were statistically tested using MS Excel, IBM SPSS (version 26), and OriginPro software packages.

Visual characterization of pollution and moisture parameters of the polluted HTV silicone rubber surface with hyperspectral imaging technology

The application of high temperature vulcanized (HTV) silicone rubber materials in transmission lines insulators has been extensive. However, with the accumulation of pollution and moisture on the surface of HTV silicone rubber, the insulation reliability gradually decreases, which may even lead to flashover. In this paper, hyperspectral imaging technology is utilized as a rapid and effective tool for the visual characterization of pollution and moisture parameters of the polluted HTV silicone rubber. Based on the analysis of reflection spectra, it has been determined that the pollution degree has a positive effect and the moisture content has a negative effect on the reflection characteristics of HTV silicone rubber, respectively. Further quantitative analysis of reflectance values at various moisture conditions reveals that exponential relationships can be observed between reflectance values and moisture contents at a certain wavelength. At the same time, linear correlations between reflectance values and pollution degrees (quantified as equivalent salt deposit density (ESDD)) at a certain wavelength are also proposed. By integrating the exponential and linear relationships, a double-exponential model is formulated to concurrently characterize the ESDD and moisture content (MC). Furtherly, from the perspective of engineering application, to enhance the model’s robustness, a set of equations combining spectral indexes and spectral shape feature parameters is initially formulated for the calculating of ESDD and MC. Given the synchronous inversion and visualization capabilities of pollution and moisture parameters of the polluted HTV silicone rubber surface, the visual characterization model serves as a valuable tool for protecting against pollution flashover failures and designing power equipment insulation.

Evaluating Surface Water Nitrogen Pollution via Visual Clustering in Megacity Chengdu

The current standards used for nitrogen pollution evaluation are lacking, and scientific classification methods are needed for nitrogen pollution to improve water quality management capabilities. This study addresses the important issue of assessing surface water nitrogen pollution by utilizing two advanced multivariate statistical techniques: self-organizing maps (SOMs) obtained using the K-means algorithm and the Hasse diagram technique (HDT). The research targets of this study are the rivers of the megacity Chengdu, China. Samples were collected on a monthly basis in 2017–2020 from different sites along the rivers, and their nitrogen pollution parameters were determined. The grouping of nitrogen pollution parameters and the clustering of sampling events using SOMs facilitate the preprocessing required for the HDT, wherein clusters are ordered according to the pre-clustered water sampling events. The results indicate that nitrogen pollution in the Chengdu River Basin, which is prominent and mainly driven by nitrate nitrogen, can be categorized into five levels. The nitrogen pollution in Tuo River is serious. Although the degree of ammonia nitrogen pollution in Jin River is higher, the pollution range is smaller. Furthermore, these results were evaluated by the SOMs and HDT to be clear and reliable. Overall, these findings can provide a basis for local environmental legislation.

Assessment of nitrate, trace elements and bacterial contamination of groundwater in ilora area of southwestern nigeria

Assessments of groundwater pollution parameters were carried out in groundwater samples collected from selected shallow hand-dug wells across Ilora township. The analysed parameters were nitrate, trace elements including, iron, cobalt, chromium, manganese, zinc, arsenic, cadmium and lead, and bacteria count in water; using spectrophotometric method, HM Metalyser 5000 and multiple tube techniques respectively. The pH of the samples was between 6.4 and 7.6 and TDS range was 50 - 640 mg/l. The concentration of nitrate (NO3) in water was 12.8 - 274 mg/l. For trace elements concentrations in µg/l ; iron (Fe): 150 – 880, Cobalt (Co): 1 – 100, Manganese (Mn): 0.01 - 140, Chromium (Cr): 0.01 – 0.31, Zinc (Zn): 1.86 - 9.97, Arsenic (As): 3.11 - 20.80, Cadmium (Cd): 0.71 - 4.76, Lead (Pb): 1.00 – 6.82. Based on the average concentration of the trace elements the order of abundance was Fe > Co > Mn > As > Zn > Pb > Cd > Cr. Total coliform count (TCC) in groundwater samples were between 18 and 370 cfu/100mL. From the evaluation of the degree of association between the parameters, a moderate to strong positive relationship occurred between Fe/Mn (0.59), Fe/Cr (0.85), Fe/TC (0.56), NO3/Co (0.56), NO3/Mn (0.48), NO3/Cd (0.51) and Mn/Pb (0.85). Presence of coliform bacteria in the groundwater samples indicated fecal contamination from surface environment. Comparing the parameters with guideline standards for drinking water, most of the hand-dug wells are contaminated with nitrate, five wells were contaminated with either arsenic and/or cadmium, while water from some of the wells may have objectionable taste due to high iron content. The high values of cadmium and arsenic in some wells are harmful to human health and appropriate treatment is needed. For bacteria contamination, deeper wells are recommended, and the water should to be treated and boiled prior to consumption.

Monitoring Trends of CO, NO2, SO2, and O3 Pollutants Using Time-Series Sentinel-5 Images Based on Google Earth Engine

Air pollution (AP) is a significant risk factor for public health, and its impact is becoming increasingly concerning in developing countries where it is causing a growing number of health issues. It is therefore essential to map and monitor AP sources in order to facilitate local action against them. This study aims at assessing the suitability of Sentinel-5 AP products based on Google Earth Engine (GEE) to monitor air pollutants, including CO, NO2, SO2, and O3 in Arak city, Iran from 2018 to 2019. Our process involved feeding satellite images to a cloud-free GEE platform that identified pollutant-affected areas monthly, seasonally, and annually. By coding in the JavaScript language in the GEE, four pollution parameters of Sentinel-5 satellite images were obtained. Following that, images with clouds were filtered by defining cloud filters, and average maps were extracted by defining average filters for both years. The employed model, which solely used Sentinel-5 AP products, was tested and assessed using ground data collected from the Environmental Organization of Central Province. Our findings revealed that annual CO, NO2, SO2, and O3 were estimated with RMSE of 0.13, 2.58, 4.62, and 2.36, respectively, for the year 2018. The annual CO, NO2, SO2, and O3 for the year 2019 were also calculated with RMSE of 0.17, 2.41, 4.31, and 4.6, respectively. The results demonstrated that seasonal AP was estimated with RMSE of 0.09, 5.39, 0.70, and 7.81 for CO, NO2, SO2, and O3, respectively, for the year 2018. Seasonal AP was also estimated with RMSE of 0.12, 4.99, 1.33, and 1.27 for CO, NO2, SO2, and O3, respectively, for the year 2019. The results of this study revealed that Sentinel-5 data combined with automated-based approaches, such as GEE, can perform better than traditional approaches (e.g., pollution measuring stations) for AP mapping and monitoring since they are capable of providing spatially distributed data that is sufficiently accurate.

Evaluation of Ti/Pt Anode Efficiency and Energy Consumption in Turbidity and Suspended Solids Removal from Paper Industry Wastewater: The Effect of pH and Support Electrolyte Type

In the research, different experimental setups were used to examine the treatment of wastewater from the paper industry using the electrooxidation method, one of the electrochemical treatment methods in the batch system. In the 2000 mL volume jacketed glass reactor utilized for the treatment of wastewater from the paper industry, 4 anode and 4 cathode sieve type plates of 7 cm x 10 cm dimensions were positioned at 0.5 cm intervals, and 1200 mL wastewater was used in the tests. Coated sieve type Ti/Pt electrodes were employed as the anode in the electrooxidation studies, and uncoated sieve type Ti electrodes were used as the cathode. It was determined that the active anodic wet surface area was 1078 cm2 . The removal rates of pollutant parameters such as turbidity and SS (Suspended Solids) in the experiments; the effects of wastewater initial pH value and supporting electrolyte type parameters were investigated. According to the results, the most effective pH value for Ti/Pt anode type at 400 rpm mixing speed was determined to be waste water natural pH (7.5), and 0.50 M NaCl was the most successful supporting electrolyte type. 96.92% Suspended Solids removal efficiency and 95.38% turbidity removal efficiency for Ti/Pt anode were achieved under ideal conditions. In addition, 312.05 kW-hour/kg COD is determined as the energy consumption value.

Temporal evaluation of surface water quality in semiarid regions: a case study of the Ouled Mellouk dam in north-western Algeria

Abstract This work aimed at evaluating the impact of human activity and geology on the surface water quality of the Ouled Mellouk dam (northwestern Algeria). Specifically, methodology aims to assess seasonal variations of several parameters (EC, TDS, pH, SO42−, Cl−, Ca2+, Na+, HCO3−, NO3−, PO43− and Mg2+, organic matter, suspended solids, BOD5, COD) from 2007 to 2013 to define the processes controlling the mineralization and pollution of the surface water. The results show high salinization recorded during the periods of heavy precipitation or flooding, due to leaching of dolomitic limestones and evaporitic deposits from the saliferous formations of the surrounding mountains. High concentrations of NO3−, NO2−, NH4+, and organic matter can instead be attributed to the use of fertilizers in agriculture. Moreover, the PCA application shows that salinization (49.92%), anthropogenic pollution (19.38%) and agricultural pollution (12%) are the most significant degradation factors, respectively. The saturation index of carbonates and gypsiferous minerals shows the carbonates precipitate before the gypsiferous minerals, which allowed the chemical elements coming from the dissolution of gypsum and halite to acquire significant contents. In addition, the evolution of biological oxygen demand and organic pollution shows slight pollution of the dam water.

Big data-driven carbon emission traceability list and characteristics of ships in maritime transportation-a case study of Tianjin Port.

As China's shipping industry continues to develop, ship emissions have become a significant source of pollutants. Consequently, it has become imperative to comprehend accurately the nature and attributes of ship pollutant emissions and understand their causation and effect as a crucial aspect of pollution control and legislation. This paper employs high-precision automatic identification system (AIS) dynamic and static data, along with pollutant emission parameters, to estimate the pollutant emissions from a ship's main engine, auxiliary engine, and boiler using a dynamic approach. Additionally, the study considers the sailing state and trajectory of the vessel and analyzes the characteristics of ship carbon emissions. Taking Tianjin Port as an example, this study conducts a multi-dimensional analysis of pollutant emissions to gain insight into the causation and effect of pollutants based on the collected big AIS data. The results show that the pollutant emissions in this region are mainly concentrated in the vicinity of Tianjin Port land port area, Dagusha Channel, and the Main Shipping Channel of Tianjin Xingang Fairway. Carbon emissions peak in September and are lower in June and December. Through accurate analysis of pollutant emission sources and emission characteristics in the region, this paper establishes the regular relationship between pollutant emissions and possible influencing factors and provides data support for China to formulate accurate pollutant emission reduction policies and regulate ship construction technology and carbon trading.

Evolution of neural network to deep learning in prediction of air, water pollution and its Indian context.

The scenario of developed and developing countries nowadays is disturbed due to modern living style which affects environment, wildlife and natural habitat. Environmental quality has become or is a subject of major concern as it is responsible for health hazard of mankind and animals. Measurements and prediction of hazardous parameters in different fields of environment is a recent research topic for safety and betterment of people as well as nature. Pollution in nature is an after-effect of civilization. To combat the damage already happened, some processes should be evolved for measurement and prediction of pollution in various fields. Researchers of all over the world are active to find out ways of predicting such hazard. In this paper, application of neural network and deep learningalgorithms is chosen for air pollution and water pollution cases. The purpose of this review isto reveal how family of neural network algorithms has applied on these two pollution parameters. In this paper, importance is given on algorithm, and datasets used for air and water pollution as well as the predicted parameters have also been noted for ease of future development. One major concern of this paper is Indian context of air and water pollution research, and the research potential presents in this area using Indian dataset. Another aspect for including both air and water pollutions in one review paper is to generate an idea of artificial neural network and deep learning techniques which can be cross applicable for future purpose.