How COVID-19 induced panic on stock price and green finance markets: global economic recovery nexus from volatility dynamics

Environmental Science and Pollution Research - This paper investigates the effect of different categories of essential COVID-19 data from 2020 to 2021 towards stock price dynamics and options...     

Dietary intake assessment of pyrethroid residues from okra and eggplant grown in peri-urban areas of Punjab,Pakistan

Environmental Science and Pollution Research - This study was designed to assess the gradual increase in the use of insecticides on vegetables and to familiarize the consumers regarding the...     

System dynamic modeling of CO<Subscript>2</Subscript> emissions and pollutants from passenger cars in Malaysia, 2040

Transportation sector is the second largest producer of greenhouse gas in Malaysia next to energy sector. It contributes to nearly 28 % of annual national carbon emissions due to its heavy dependency of hydrocarbons such as gasoline. If not properly managed, carbon dioxide emissions per capita are expected to nearly double in the next 5 years. Lack of interdisciplinary study on this sector has caused proper mitigation initiatives to be delayed, compounding the damage to the ecosystem. The objective of this study is to develop a dynamic probabilistic model to determine emissions and pollutants of transportation system in Malaysia using Analytica software, with focus on passenger cars for its large number over other vehicle classes. Several vehicle fleet management policies based on several key governmental, industrial and stakeholder’s intervention have been constructed and analyzed for a period of 25 years. This analysis found that greenhouse gas emissions and pollutants in 2040 can be reduced by up to 80 %, compared to emissions of 2020, without any adverse effect on vehicle demand nor the economy. However, without proper intervention, personal transportation system in Malaysia will generate nearly 80,000 kilotons of greenhouse gas annually by the year 2040.     

Physiopathology and effectiveness of therapeutic vaccines against human papillomavirus

Environmental Science and Pollution Research - Human papillomavirus (HPV) is a well-known sexually transmitted disorder globally. Human papillomavirus (HPV) is the 3rd most common cancer that...     

Spatial and temporal characterization of trace elements and nutrients in the Rawal Lake Reservoir,Pakistan using multivariate analysis techniques

Rawal Lake Reservoir is renowned for its ecological significance and is the sole source of drinking water of the third largest city of Pakistan. However, fish kill in recent years and anthropogenic impacts from human-related activities in its catchment area have resulted in deterioration of its surface water quality. This study aims to characterize spatial and temporal variations in surface water quality, identify contaminant sources, and compare their levels with quality guidelines. Surface water samples were collected from 10 sites and analyzed for 27 physicochemical parameters for a period of 2 years on a seasonal basis. Concentration of metals in surface water in pre-monsoon were in the order: Fe > Mg > Ca > Mn > Zn > Ni > Cr > Cu > Co > Pb, whereas in post-monsoon, the order of elemental concentrations was: Ca > Mg > Na > Fe > K > Zn > Cr > Li > Pb > Co > Ni > Cu > Mn > Cd. Metals (Ni, Fe, Zn, and Ca), pH, electrical conductivity (EC), dissolved oxygen (DO), chemical oxygen demand (COD), and nutrients (PO₄³⁻, NO₃–N, and SO₄²⁻) were measured higher in pre-monsoon, whereas concentration of Cu, Mn, Cr, Co, Pb, Cd, K, Na, Mg, Li, Cl⁻, and NH₄–N were recorded higher in post-monsoon. Results highlighted serious metal pollution of surface water. Mean concentration of Zn, Cd, Ni, Cu, Fe, Cr, and Pb in both seasons and Mn in post-monsoon were well above the permissible level of surface water quality criteria. Results stress the dire need to reduce heavy-metal input into the lake basin and suggest that heavy-metal contamination should be considered as an integral part of future planning and management strategies for restoration of water quality of the lake reservoir.     

Spatial Distribution of the Annual Atmospheric Carbon Dioxide in the Contiguous USA and Their Controlling Factors

Environmental Modeling & Assessment - Analyzing the geographical distribution of carbon dioxide (CO2) is essential for understanding the influence and structural nature of area-specific...     

Impact of climate factors on cyanobacterial dynamics and their interactions with water quality in South Taihu Lake,China

Cyanobacterial bloom events in South Taihu Lake cause serious water quality problems and disturb aesthetic view of lake’s environment. In this study, correlations between cyanobacterial blooms and hydro-meteorological factors, including water quality, temperature and precipitation were investigated. Results demonstrated that South Taihu Lake was heavily affected by cyanobacteria and the proliferation of cyanobacteria due to variations in hydro-meteorological factors and water quality conditions. Water quality parameters, including COD, NH₃-N, TN and TP improved significantly since 2008 even at an elevated cyanobacterial bloom situation. Correlation analyses have shown that the development of cyanobacterial density and chlorophyll a concentration was sensitive to a wider temperature variation. The optimum temperature for cyanobacteria was 20°C, while extremely low and high temperatures were found to suppress their growth. Moreover, unusual rainfall patterns were measured during the study period (2003–2009), which showed an adverse impact on cyanobacterial development. Findings from this study suggested that seasonal lake’s water quality monitoring; suitable treatment of cyanobacterial blooms and strict policy implementation can solve the water quality issues in highly eutrophic lakes like Taihu.