Carbofuran-induced effects on acetylcholinesterase (AChE) in erythrocytes and liver of Cyprinus carpio

A study was conducted to determine the effects of long-term exposure to carbofuran on erythrocyte and liver acetylcholinesterase (AChE) activity in Cyprinus carpio, and assess which tissue was more sensitive to pesticide exposure examining this enzyme. Fish were allowed to accilimatize in toxicant-free water for 24 days after 60-day exposure. AChE activity was determined with a spectrophotometer using acetylthiocholine iodide as a substrate in erythrocytes and liver. Enzymic activity of erythrocytes and liver decreased over time. A higher degree of enzyme inhibition was observed in erythrocyte compared to liver. The degree of enzyme inhibition was positively correlated with exposure time. When exposed fish were transferred to clean water, recovery was greater in erythrocytes than liver. Erythrocyte AChE activity recovered after 18 days, while it required 21 days in liver. The findings of this study indicate that erythrocyte AChE is more sensitive to carbofuran than liver. The greater sensitivity of erythrocyte AChE suggests that it may be more useful as a biomarker for monitoring status of pollution in freshwater bodies.     

Effect of slow release nitrogenous fertilizers and biochar on growth,physiology, yield,and nitrogen use efficiency of sunflower under arid climate

Environmental Science and Pollution Research - Sunflower plants need nitrogen consistently and in higher amount for optimum growth and development. However, nitrogen use efficiency (NUE) of...     

Conditional effect of governance quality on the finance-environment nexus in a multivariate EKC framework: evidence from the method of moments-quantile regression with fixed-effects models

This paper investigates the mitigating effect of governance quality on the finance-environment nexus in a multivariate EKC framework in 123 selected countries during the 1990–2017 period. We mainly employ the method of moments-quantile regression (MM-QR) with the fixed-effects model, among others. First, the MM-QR estimator reveals that financial development reduces environmental quality more significantly in countries with initially higher levels (the 75^th and 90^th quantiles) of CO₂ emissions than in other countries (the 25^th and 10^th quantiles). Second, the attenuating effect of governance quality on the finance-environment nexus is more remarkable in nations with low initial levels (the 25^th and 10^th quantiles) of CO₂ emissions. Third, we find that the marginal positive effect of financial development on CO₂ emissions is smaller under a good regulatory framework than under corruption control and the rule of law, especially in the top emitters (the 75^th and 90^th quantiles). Fourth, unlike oil, which has a considerable negative impact on the environmental quality of the major emitters, renewable energy usage reduces CO₂ emissions in countries in all quantiles, primarily in the lowest quantiles. Fifth, the findings also show that urbanization dramatically worsens environmental quality in all economies, particularly those in the lowest quantiles. Finally, we confirm that the EKC hypothesis holds in all countries across different quantiles. The study’s final section discusses policy implications for sustainable development in all countries.

     

Analysis of Meteorological Drought Pattern During Different Climatic and Cropping Seasons in Bangladesh

Drought is one of the most frequent natural disasters in Bangladesh which severely affect agro‐based economy and people's livelihood in almost every year. Characterization of droughts in a systematic way is therefore critical in order to take necessary actions toward drought mitigation and sustainable development. In this study, standardized precipitation index is used to understand the spatial distribution of meteorological droughts during various climatic seasons such as premonsoon, monsoon, and winter seasons as well as cropping seasons such as Pre‐Kharif (March‐May), Kharif (May‐October), and Rabi (December‐February). Rainfall data collected from 29 rainfall gauge stations located in different parts of the country were used for a period of 50 years (1961‐2010). The study reveals that the spatial characteristics of droughts vary widely according to season. Premonsoon droughts are more frequent in the northwest, monsoon droughts mainly occur in the west and northwest, winter droughts in the west, and the Rabi and Kharif droughts are more frequent in the north and northwest of Bangladesh. It is expected that the findings of the study will support drought monitoring and mitigation activities in Bangladesh.     

Potential Impact of Climate Change on Residential Energy Consumption in Dhaka City

This study aimed to assess the impacts of climate change on residential energy consumption in Dhaka city of Bangladesh. The monthly electricity consumption data for the period 2011–2014 and long-term climate variables namely monthly rainfall and temperature records (1961–2010) were used in the study. An ensemble of six global circulation models (GCMs) of coupled model intercomparison project phase 5 (CMIP5) namely, BCCCSM1-1, CanESM2, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, and NorESM1-M under four representative concentration pathway (RCP) scenarios were used to project future changes in rainfall and temperature. The regression models describing the relationship between historical energy consumption and climate variables were developed to project future changes in energy consumptions. The results revealed that daily energy consumption in Dhaka city increases in the range of 6.46–11.97 and 2.37–6.25 MkWh at 95% level of confidence for every increase of temperature by 1 °C and daily average rainfall by 1 mm, respectively. This study concluded that daily total residential energy demand and peak demand in Dhaka city can increase up to 5.9–15.6 and 5.1–16.7%, respectively, by the end of this century under different climate change scenarios.     

Agricultural GHG emission and calorie intake nexus among different socioeconomic households of rural eastern India

A study was conducted to examine the interrelationships among socioeconomic factors, household consumption patterns, calorie intake and greenhouse gas emissions factors in rural eastern India based on household survey data. Findings indicated that higher monthly per capita incomes (12.1–80.1$) were associated with greater average calorie intakes (2021–2525 kcal d^?1). As estimated by the FEEDME model, in total 17.2% of the population was calorie malnourished with a regional disparity of 29.4–18.2% malnourishment. Greenhouse gas (GHG) emissions were calculated only on the basis of crop and livestock production and consumption. Rice accounted for the highest share of total GHG emissions, on average 82.6% on a production basis, which varied from 58.1% to 94.9% in regional basis. Rice contributed the greatest share (~?65% and 66.2%) in terms of both calories and GHG emissions (CO₂ eq y^?1), respectively, on a consumption basis. We conclude that extensive rice farming and increasing animal product consumption are dominant factors in the higher carbon footprint in this region and are likely to further increase with increase in per capita income. This study provides useful information to help for better crop planning and for fine-tuning food access policy, to reduce carbon footprint and calorie malnutrition.

     

Multivariate analysis of accumulation and critical risk analysis of potentially hazardous elements in forage crops

Environmental Monitoring and Assessment - Few estuaries remain unaffected by water management and altered freshwater deliveries. The Caloosahatchee River Estuary is a perfect case study for...     

Bacillus safensis with plant-derived smoke stimulates rice growth under saline conditions

Environmental Science and Pollution Research - Salinity is a worldwide environmental problem of agricultural lands. Smoke and plant growth-promoting bacteria (PGPR) are individually used to improve...     

Nature and prevalence of non-additive toxic effects in industrially relevant mixtures of organic chemicals

The concentration addition (CA) and the independent action (IA) models are widely used for predicting mixture toxicity based on its composition and individual component dose–response profiles. However, the prediction based on these models may be inaccurate due to interaction among mixture components. In this work, the nature and prevalence of non-additive effects were explored for binary, ternary and quaternary mixtures composed of hydrophobic organic compounds (HOCs). The toxicity of each individual component and mixture was determined using the Vibrio fischeri bioluminescence inhibition assay. For each combination of chemicals specified by the 2ⁿ factorial design, the percent deviation of the predicted toxic effect from the measured value was used to characterize mixtures as synergistic (positive deviation) and antagonistic (negative deviation). An arbitrary classification scheme was proposed based on the magnitude of deviation (d) as: additive (10%, class-I) and moderately (10 < d  30%, class-II), highly (30 < d  50%, class-III) and very highly (>50%, class-IV) antagonistic/synergistic. Naphthalene, n-butanol, o-xylene, catechol and p-cresol led to synergism in mixtures while 1, 2, 4-trimethylbenzene and 1, 3-dimethylnaphthalene contributed to antagonism. Most of the mixtures depicted additive or antagonistic effect. Synergism was prominent in some of the mixtures, such as, pulp and paper, textile dyes, and a mixture composed of polynuclear aromatic hydrocarbons. The organic chemical industry mixture depicted the highest abundance of antagonism and least synergism. Mixture toxicity was found to depend on partition coefficient, molecular connectivity index and relative concentration of the components.