Exploring the Effects of Economic Complexity and the Transition to a Clean Energy Pattern on Ecological Footprint From the Indian Perspective

The study explores the association between economic complexity, globalization, renewable and non-renewable energy consumption on the ecological footprint in the case of India from 1990–2018. The autoregressive distributed lag (ARDL) is applied to measure the long-run elasticity, while the vector error correction model (VECM) is applied to classify the causal path. The empirical findings demonstrate that economic complexity, globalization process, and renewable energy consumption play a dominant role in minimizing environmental degradation. In contrast, economic growth and non-renewable energy consumption are more responsible for increasing the pollution level in both the short and long run. Furthermore, the VECM outcomes disclose that there is long-run causality between ecological footprint and economic complexity. Moreover, the empirical outcomes are robust to various robustness checks performed for analysis to the consistency of our main results. The Indian government/policymakers should encourage a more environmentally friendly production process and eco-friendly technologies in exports to minimize environmental degradation.

Assessment of the Ecological Risk from Heavy Metals in the Surface Sediment of River Surma, Bangladesh: Coupled Approach of Monte Carlo Simulation and Multi-Component Statistical Analysis

River sediment can be used to measure the pollution level in natural water, as it serves as one of the vital environmental indicators. This study aims to assess heavy metal pollution namely Copper (Cu), Iron (Fe), Manganese (Mn), Zinc (Zn), Nickel (Ni), Lead (Pb), and Cadmium (Cd) in Surma River. Further, it compares potential ecological risk index values using Hakanson Risk Index (RI) and Monte Carlo Simulation (MCS) approach to evaluate the environmental risks caused by these heavy metals. in the study area. With obtained results, enrichment of individual heavy metals in the study area was found in the order of Ni > Pb > Cd > Mn > Cu > Zn. Also, variance in MCS index contributed by studied metals was in the order of Cd > Pb > Ni > Zn > Cu. None of the heavy metals, except Ni, showed moderate contamination of the sediment. Risk index values from RI and MCS provide valuable insights in the contamination profile of the river, indicating the studied river is currently under low ecological risk for the studied heavy metals. This study can be utilized to assess the susceptibility of the river sediment to heavy metal pollution near an urban core, and to have a better understanding of the contamination profile of a river.

Forecasting of outdoor air quality index using adaptive Neuro Fuzzy Inference System

Introduction: The estimation of air pollution level is well indicated by Air Quality Index (AQI), which tells how unhealthy the ambient air is and how polluted it can become in near future. Hence, the predictions or modeling of AQI is always of greater concern among researchers and this present study aims to develop such a model for forecasting the AQI. Materials and methods: A combination of Artificial Neural Network (ANN) and Fuzzy logic (FL) system, called Adaptive Neuro-Fuzzy Inference System (ANFIS) have been considered for model development. Daily air quality data (PM2.5 and PM10) and meteorological data (temperature and humidity) over a period of March 2020 to March 2021 were used as the input data and AQI as the output variable for the ANFIS model. The performances of models were evaluated based on Root Mean Square Error (RMSE), Regression coefficient (R2) and Average Absolute Relative Deviation (AARD). Results: A total of 100 datasets is split into training (70), testing (15) and simulation (15). Gaussian and Constant membership functions were employed for classifications and the final index consisted of 81 inference (IF/THEN) rules. The ANFIS Simulation result shows an R2 and RMSE value of 0.9872 and 0.0287 respectively. Conclusion: According to the results from this study, ANFIS based AQI is a comprehensive tool for classification of air quality and it is inclined to produce accurate results. Therefore, local authorities in air quality assessment and management schemes can apply these reliable and suitable results.

Is it possible to turn a diesel engine into a less pollutant device?

The current tendency in the eastern part of Europe is to modify old diesel engines with the purpose of improving characteristics in terms of horsepower and torque, but also to reduce the generated pollution. The diesel engines are still in use, against to the tendencies of renouncing to their support, at least in larger urban & industrial areas, where the pollution level, especially the particulate matter (particles PM10, PM2.5) and ozone concentrations, also the NOx are supposed to be generated mostly by diesel engine vehicles. The paper presents results concerning the influence of modifying the diesel engine control unit’s parameters, such as injection quantity, start of injection, intake air pressure and all the others correlated for better performance. The article brings into attention possibilities to reduce the exhaust pollution concentrations, correlated by simultaneous ways of improving the external characteristics of the engine by modifying the engine control unit’s parameters. Measurement results of a compression ignited internal combustion engine before and after the retrofitting, by reparametrization, meaning changing the parameters are presented and discussed.

A STUDY ON AIR POLLUTION TOLERANCE INDEX (APTI) AND ANTICIPATED PERFORMANCE INDEX (API) OF SOME PLANTS

Due to industrialization, urbanization and increasing number of vehicles air pollution has turn out to be serious problem today. Now a days particulate matter shows the undesirable effects on plants, animals and human beings also. Tree plantation programme is the best ways to control the air pollution. Most of the plants filter the air by their aerial elements. Vegetation naturally cleanses the atmosphere by absorbing gases and some particulate matters through leaves so they work as sink for air pollution and reduce pollution level in atmosphere. Leaves function as an efficient pollutant trapping device. Air pollution can directly affects plants via leaves or indirectly via soil acidification. Air pollution tolerance index (APTI) is an intrinsic quality of trees to control air pollution problems. The trees higher tolerance index are tolerance towards air pollution and can be used a source to control air pollution. Air pollution tolerance index can be used as an indicator of rate of air pollution. By combining biochemical and aggregate factors the anticipated performance index (API) is prepared which is used as development of green belt. Thus, the assessment of APTI and API potential of different trees are used to control air pollution.

SURFACE WATER QUALITY IN KHARKIV RECREATIONAL AREAS: 2006-2020

The aim of the paper is to assess dynamics of water quality in four main recreational areas in Kharkiv and to develop recommendations for water quality improvement. Methods. Field and laboratory methods and analytical data processing. Results. The paper presents analysis of dynamics in water quality for four main recreational areas located in Kharkiv: Zhuravlevskiy Hydropark, Oleksiivskiy Lugopark, Udyanskiy Hydropark and Osnovyanske Lake. Period of study: 2006-2020, time: May-June and August-September. Average data are presented. Samples were analysed at certified Laboratory of Analytical Chemical Research of the Karazin Institute of Environmental Sciences. Laboratory data were compared with national UA standards and European ones. Conclusions were made for the following key parameters: dissolved oxygen and BOD5, total mineralization, biogenic substances content, oil products and surfactants, toxic heavy metals content. There is no specific dynamics on the pollution level. Conclusions. The following recommendations for improvement of water quality were developed: (i) to preform regular monitoring of water quality; (ii) to introduce regular and systematic control by one local authority; (iii) to improve infrastructure of recreational areas; (iv) to introduce regular cleaning of the recreational areas; (v) to install bio-WC; (vi) to install additional waste containers (preferably with separate waste collection); (vii) plant trees for better isolation from highways; (viii) to improve level of water treatment on WWTP; (ix) to create nature protected areas along rivers

FUNCTIONAL STATE OF THE MARINE MICROALGAE CULTURES AS AN INDICATOR OF THE WATER POLLUTION LEVEL OF THE SEVASTOPOL BAY

The possibility of using cultures of Black Sea planktonic microalgae of different taxonomic affiliation to assess the quality of the aquatic environment based on the assessment of their functional state is shown. The research was carried out on the diatom Phaeodactylum tricornutum, three dinoflagellates species Prorocentrum cordatum, Prorocentrum pusillum and Gyrodinium fissum, as well as the coccolithopho-ride Emiliania huxleyi. It was found that the waters of the Sevastopol Bay in the period from May to August 2021 in 50% of cases had a weak inhibitory effect on the growth of the tested species. In other cases, algae growth was either stimulated or the effect of pollution on cultures was not revealed. The need for using several types of algae in carrying out complex work on water biotesting of the coastal are-as of the Black Sea is highlighted.

Zooplankton Diversity Indices for the Assessment of Perennial Freshwater Body in Bishnupur, Bankura, West Bengal

The status of health of any aquatic ecosystem is largely dependent on the diversity and density of zooplankton inhabiting the water body. Zooplankton are considered to be the most vital primary consumer in any aquatic ecosystem. At the same time, they also influence to a greater extent in determining the total productivity of an aquatic body. The present study is an attempt to estimate the diversity of zooplankton and to find out the richness, evenness, of the freshwater perennial aquatic body, Lalbundh of Bishnupur, Bankura.The study was carried out during December 2018 to November 2019. The whole period of study was divided into four major seasons viz winter (December2018 to February2018), Summer (March2019to May 2019), Monsoon (June 2019 to August 2019) and post monsoon (September 2019 to November 2019). Collection of the zooplankton samples and their quantitative analysis was done following the standard procedures. During the whole period of study 18 different species of zooplankton have been identified from the study area. Out of them 7 species belong to the Rotifera group, 6 species belong to Cladocera group, 3 species of Copepoda group and 2 species of Ostracoda group. Rotifera group comprise the dominant of all the groups constituting 39% of the total zooplankton species, followed by Cladocera (33%), Copepoda(18%) and Ostracoda (11%). The range of Shannon diversity index value of zooplankton varies from 2.76 to 2.88. The species richness value varies from 2.45 (winter) to 2.56 (monsoon). Evenness value varies from 0.95 in summer to0.98in monsoon. Zooplankton diversity indices values of Lalbundh give a clear indication of light condition of pollution level of the water body. The main reason behind the pollution of this perennial water body may be the floating dead and decomposed macrophytes in it. They should be removed as far as possible at regular intervals so that the pollution level can be reduced and the water body can be more efficiently used for pisciculture practices.

Nexus Between CO2 Emissions, Energy Use and Economic Growth in Nepal

Background: Economic growth in different economies comes with a cost of environmental degradation. The environment-growth nexus has come to the spotlight since scientists as well as policy-makers point out the threat of climate change and global warming all around the world. Nepal faces problems of pollution day by day raising a question about sustainable growth in the country. Such sustainability can be achieved by exploiting the water resources of the country which can be further used to generate cleaner forms of energy. Objective: This paper examines the interconnection between environmental degradation and economic growth in Nepal under the Environmental Kuznets curve’s framework and causal framework. These frameworks also incorporate energy variables such as electricity production, electricity and oil consumption at a disaggregated level to understand the energy growth nexus in Nepal. Method: The Auto-Regressive Distributed Lag model followed by TY Non-Granger Causality tests and variance decompositions are incorporated in the study to examine the EKC hypothesis and the nexus between energy and growth is analyzed through a multivariate framework. Result: Our result does not show the presence of the EKC hypothesis in the case of Nepal. However, the causal framework indicated that a percentage increase in electricity generation would lead to a reduction in carbon dioxide by 0.7%. The variance decomposition results showed that the impact of CO2 on GDP would decrease with horizons getting longer. On the other hand, the impact of electricity generation on CO2 on was found to be 78% in the longer horizon. Conclusion: Nepal should harness its potential of generating hydroelectricity to reduce environmental pollution as well as increase economic growth. Substituting the cleaner form of energy such as hydroelectricity can help in reducing the consumption of fossils and fuels as well as help in mitigating the pollution level in Nepal. This will further allow Nepal to be self-reliant since it has huge potential for generating hydroelectricity.

Screening Approach for Short-Term PM2.5 Health Co-Benefits: A Case Study from 15 Metropolitan Cities around the World during the COVID-19 Pandemic

Fifteen cities across the world have been selected to investigate the public health co-benefits of PM2.5 reduction, during a period when various non-pharmaceutical interventions (NPIs) were adopted in the COVID-19 pandemic. Through applying a public health model, AirQ+, substantial spatial variations of global public health co-benefits were identified. Differences in seasonal air quality and population baselines were key underlying factors. For cities in North America, NPIs were introduced during the low pollution season, generating no co-benefits. On the other hand, tremendous health co-benefits were observed for cities in India and China, due to the high PM2.5 background with a large population. Among all, New Delhi has received the largest co-benefits, which saved over 14,700 premature deaths. As the pollution level (i.e., 45 μg m−3) with NPIs still exceeded the air quality standard, more rigorous emission controls are urgently needed to protect the public′s health in India. At last, a novel and practical tool for co-benefit screening was developed using data from one of the global measurement networks (i.e., IQAir).