Fintech and environmental efficiency: The dual role of foreign direct investment in G20 nations.

This study investigates the relationship between financial technology (fintech) and environmental efficiency across G20 countries, emphasizing the moderating effect of foreign direct investment (FDI) from 2010 to 2022. Employing Data Envelopment Analysis (DEA) through both Slack-Based Measure (SBM) and Epsilon-Based Measure (EBM), alongside Tobit regression and the Generalized Method of Moments (GMM) for analytical rigor, the research reveals that fintech exerts a positive influence on environmental efficiency within these countries. Furthermore, it demonstrates that FDI contributes to enhancing environmental efficiency. However, when FDI is combined with fintech investments, it yields a negative impact. This detrimental effect stems from FDI's emphasis on short-term gains, rapid expansion, and a globally oriented supply chain that favors cost efficiency at the expense of sustainability. The study highlights the necessity for investments in fintech that comply with environmental standards and offers policy recommendations to improve environmental efficiency. It urges policymakers to promote environmentally sustainable investment practices within the fintech sector to aid in achieving sustainable development goals.

Assessment of heavy metals level in chicken with indeterminate analysis in localities of Lahore, Pakistan.

The poultry industry is a significant source of animal protein, vitamins, and minerals, particularly through the consumption of chicken meat. In order to conduct the study, 100 samples of liver, chicken feed, and drinking water were collected in nearby areas of Lahore. The investigation aims to detect the presence of specific heavy metals in the collected samples. For this purpose, atomic absorption spectroscopy (AAS) was used to detect heavy metals after proper preparation of the samples. The experimentally observed data were analyzed through a novel statistical approach known as neutrosophic statistics. It was observed that copper (Cu), zinc (Zn), and cadmium (Cd) were the most prominent metals detected with contamination above the safe limits (for chicken drinking water (Zn = 23.09±13.67 mg/L, Cu = 3.84±3.04 mg/L, Cd = 0.805±0.645 mg/L, Pb = 0.275±0.095 mg/L, As = 0.982±0.978 mg/L), for chicken feed (Zn = 2.705±0.715 mg/kg, Cu = 1.85±0.53 mg/kg, Cd = 3.065±1.185 mg/kg, Pb = 0.215±0.175 mg/kg, As = 0.68±0.22 mg/kg), and chicken's liver (Zn = 3.93±0.66 mg/kg, Cu = 1.2±0.52 mg/kg, Cd = 0.07±0.05 mg/kg, Pb = 0.805±0.775 mg/kg, As = 1.05±0.8 mg/kg)). Similarly, the statistical analysis leads that the findings emphasize the importance of monitoring and mitigating heavy metal contamination in the poultry industry to ensure the safety and quality of poultry products.

Hidden Markov Models based intelligent health assessment and fault diagnosis of rolling element bearings.

Hidden Markov Models (HMMs) have become an immensely popular tool for health assessment and fault diagnosis of rolling element bearings. The advantages of an HMM include its simplicity, robustness, and interpretability, while the generalization capability of the model still needs to be enhanced. The Dempster-Shafer theory of evidence can be used to conduct a comprehensive evaluation, and Stacking provides a novel training strategy. Therefore, the HMM-based fusion method and ensemble learning method are proposed to increase the credibility of quantitative analysis and optimize classifiers respectively. Firstly, vibration signals captured from bearings are decomposed into intrinsic mode functions (IMFs) using ensemble empirical mode decomposition (EEMD), and then the Hilbert envelope spectra of main components are obtained; Secondly, multi-domain features are extracted as model input from preprocessed signals; Finally, HMM-based intelligent health assessment framework and fault diagnosis framework are established. In this work, the life cycle health assessment modeling is performed using a few training samples, the bearing degradation state is quantitatively evaluated, normal and abnormal samples are effectively distinguished, and the accuracy of fault diagnosis is significantly improved.

A modified mental state assessment tool for impact analysis of virtual reality-based therapeutic interventions in patients with cognitive impairment.

Objectives: This work has developed a modified mental state assessment tool for impact analysis of therapeutic interventions for patients with cognitive impairment. This work includes a pilot study to validate the proposed tool and assess the impact of virtual reality-based interventions on patient well-being, which includes assessment of cognitive ability and mood. Methods: The suggested tool's robustness and reliability are assessed in care home facilities with elderly residents over the age of 55. Because of the repetitive nature of the pilot study, test-retest strategy for Cronbach's alpha coefficient is employed to validate the internal consistency of the proposed tool over time. Qualitative and quantitative analyses are performed on the collected data to draw inferences on the impact of virtual reality-based interventions on patients with cognitive impairments. Results: The Cronbach's alpha coefficient value shows that the proposed tool's resilience is comparable to that of its pre-intervention counterparts. The Cronbach's alpha coefficient values are determined for Pre-virtual reality and Post-virtual reality interventions, which include 116 virtual reality sessions for 52-participant, and three cohorts of virtual reality sessions for 21 participants. These values for a majority of the interventions remained within the acceptable range of 0.6-0.8. Conclusions: The proposed modified mental state assessment tool is observed to be a reliable tool for investigating the impact of virtual reality-based interventions on patients with cognitive impairments. One of the notable significance of the proposed tool is that this allows for resource allocation for such interventions to be tailored to the needs of the patient, leading to greater therapeutic efficacy and resource efficiency.

Households food consumption pattern in Pakistan: Evidence from recent household integrated economic survey.

The analysis of food consumption pattern is a primary concern of any developing country because it is related with food security. Pakistan is one of the emerging nations of the developing world. Due to the similarities and differences in households' food consumption behavior, income distribution, the effects of alternative tax structures, cost-benefit analyses, and the choice of cost of living index, the study of households' food consumption pattern is crucial for a developing nation like Pakistan. Furthermore, for Pakistan's food security in the present and the future, an analysis of food consumption pattern is crucial. The main objective of this study is to analyze the households' food consumption pattern. Linear Approximation Almost Ideal Demand System (LA/AIDS) is applied using data from Household Integrated Economic Survey (HIES) for the year 2018-19. This study makes a significant contribution by estimating household age composition elasticities, which were absent from earlier studies. Results from the income elasticities reveal that milk, meat, and fruits are luxuries food items. Similarly, on the basis of inelastic income elasticities we declared cereals, pulses, vegetables, sugar, and ghee as necessity food items. Results from the compensated own price elasticities show that the eight food commodity groups have inelastic own-price elasticities. This implies that these food commodities are integral food items of household diet. Results from the compensated cross-price elasticities shows that cereals and pulses, cereals and vegetables, pulses and vegetables, milk and fruits, meat and fruits, and milk and ghee are gross substitutes. On the other hand, pulses and meat, pulses and fruits, and ghee and meat are gross complements. According to the findings of the household age composition elasticities, adding children to a household significantly increases its sugar consumption while significantly reducing its fruit consumption. Any increase in the size of the household by an adolescent, adult, or a person in their middle age results in a significant increase in the consumption of cereals and a significant drop in the consumption of fruits. Finally, any increase in the size of the households brought about by an elder resulted in a significant rise in the consumption of cereals and a significant drop in the consumption of vegetables.

Food waste: causes and economic losses estimation at household level in Pakistan.

Food waste is one of the major sustainability issues that need to be addressed due to its negative impacts on the economy, environment, and food security. To develop food waste reduction policies on regional and global level, it is mandatory to have a clear understanding of the various factors prompting food waste at household level and the extent of the economic losses incurred by food waste. Reducing food waste can decrease household expenditure on food, freeing resources for health, education, and well-being. The current study was aimed to (1) examine the food waste behavior of the respondents and to (2) determine the level of monetary losses from food waste. To address these objectives, a questionnaire survey and sample of food waste generated during 24 h were collected from 51 households in Tehsil Kahror Pakka, District Lodhran, Punjab, Pakistan. The survey focus was on levels of food waste and respondents' knowledge and behaviors about food waste. Economic estimation of food waste was also done. In the survey, respondents from both high- and low-income households revealed that their fruit and vegetables (31%; 32%) and peel and scrap (53%; 48%) losses were higher while egg losses (4%; 4%) were lower among various food waste categories. Wanting to eat fresh food and having no time to save food were the reasons for food waste. Monetary losses from food waste (US$ 12.8/Rs. 3677.01 per capita per annum) were higher in high-income households compared to low-income households.

Empirical nexus between financial inclusion and carbon emissions: Evidence from heterogeneous financial economies and regions.

We aim to investigate the empirical nexus between carbon emissions and financial inclusion for a panel of 74 countries from 2004 to 2020 based on the environment kuznets curve (EKC). Using the advanced panel data analysis framework of Driscoll-Kraay, Generalised linear model, and Prais-Winsten test for the entire sample and heterogeneous subsamples, we document an inverted U-shape relationship between carbon emissions and inclusive financial system. Notably, an inverted U-shape relationship is established in developed, emerging and frontier economies except in standalone economies. Furthermore, the analysis of region-wise subsamples reveals that nonlinear relationship varies across regions. The heterogeneous response of financial inclusion in curtailing environmental degradation provides vital policy insights. It suggests that financial inclusion can be used as a mitigation measure based on well-structured and robust regulatory and legal frameworks. These frameworks would create synergy effects of financial inclusion in designing policies and addressing issues related to sustainable development and climate change.

Cholinesterase activity as a potential biomarker for neurotoxicity induced by pesticides in vivo exposed Oreochromis niloticus (Nile tilapia): assessment tool for organophosphates and synthetic pyrethroids.

Organophosphates (OPs) and synthetic pyrethroids (SPs) are the most popular broad spectrum pesticides, used in agriculture as they have a strong pesticidal activity while also being biodegradable in the environment. The present study aimed to demonstrate the effects of these pesticides on the Acetylcholinesterase (AChE) activity in brain, gills and body muscles of Oreochromis niloticus - an important enzyme for the assessment and biomonitoring pollution caused by neurotoxins in the environment. The fish were exposed for 24 and 48 h to the LC0 concentrations of the malathion (1.425 mg/L), the chlorpyrifos (0.125 mg/L) and the λ-cyhalothrin (0.0039 mg/L), respectively. The activity of the AChE was significantly increased (p < 0.05) at 24 h and decreased at 48 h (except for the chlorpyrifos-treated brain and gills while tissues had shown no activity at 48 h's exposure) in all pesticides-treated tissues. The maximum increase in the activity and inhibition in the AChE activity were recorded as +92% and -52% in the chlorpyrifos and the lambda-cyhalothrin exposed brain tissues, respectively. Thus, the alterations in the AChE activities indicated that the applied pesticides are highly neurotoxic to fish and the enzyme (AChE) could be used as a useful biomarker for estimation of water pollution.

Comparing asymmetric price efficiency in regional ESG markets before and during COVID-19.

The ever-emerging environmental, social, and governance (ESG) concerns have received significant attention of policymakers, governments, regulation bodies, and investors. Considering the markets volatilities due to economic and financial uncertainties that can drive the informational price inefficiencies across the markets, this study compares the asymmetric price efficiency of regional ESG markets by using an asymmetric multifractal detrended fluctuation analysis before and during COVID-19 crisis. We then examine whether global factors influence the asymmetric efficiency of regional ESG markets. Our findings reveal that COVID-19 outbreak reduced the efficiency of regional ESG markets, except for Europe, which sustained its efficiency even during the pandemic. Moreover, global factors drive the efficiency of regional ESG markets significantly before and during COVID-19. A major implication of our findings stems from the fact that a contagion reduces the efficiency of the markets while stable economic conditions make those markets informationally efficient.

Temperature and particulate matter as environmental factors associated with seasonality of influenza incidence - an approach using Earth observation-based modeling in a health insurance cohort study from Baden-Württemberg (Germany).

BACKGROUND: Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones. OBJECTIVES: We examined influences of medium-term residential exposure to fine particulate matter (PM2.5), NO2, SO2, air temperature and precipitation on influenza incidence. METHODS: To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input. RESULTS: In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM2.5 and NO2. Computation of stressor-specific gains revealed up to 3499 infections per 100,000 AOK clients per year that are attributable to lowering ambient mean air temperature from 18.71 °C to 2.01 °C. Stressor specific gains were also substantial for fine particulate matter, yielding up to 502 attributable infections per 100,000 clients per year for an increase from 7.49 µg/m3 to 15.98 µg/m3. CONCLUSIONS: Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.

Intellectual capital and financial performance: A comparative study.

Intellectual Capital (IC) is a driving force behind the financial performance of non-financial firms. Investing in intellectual and physical capital allows companies to optimize their financial performance by maximizing resource utilization. This study aims to determine whether IC efficiency impacts the financial performance of listed Pakistani and Indian companies between 2010 and 2020. Return on Assets (ROA) and Return on Equity (ROE) are used to calculate financial performance, and IC is calculated using the modified Value-Added Intellectual Coefficient (MVAIC) model. Regression analysis is performed using the STATA software developed by the South Texas Art Therapy Association. Human Capital (HC), Structural Capital (SC), and Capital Employed (CE) have a significant impact on Pakistani and Indian firms' financial performance. Resource-based theory (RBT) supports these findings. The findings should provide management with a prompt to improve financial performance and emphasize the importance of IC. A rare study has addressed the impact of IC on firm financial performance using the MVAIC model, rather than the VAIC model, in Pakistan and India.

Determining dependence, centrality, and dynamic networks between green bonds and financial markets.

We adopted a network approach to examine the dependence between green bonds and financial markets. We first created a static dependency network for a given set of variables using partial correlations. Secondly, to evaluate the centrality of the variables, we illustrated with-in system connections in a minimum spanning tree (MST). Afterward, rolling-window estimations are applied in both dependency and centrality networks for indicating time variations. Using the data spanning January 3, 2011 to October 30, 2020, we found that green bonds and commodity index had positive dependence on other financial markets and are system-wide net contributors before and after COVID-19. Time-varying dynamics illustrated heightened system integration, particularly during the crisis periods. The centrality networks reiterated the leading role of green bonds and commodity index pre- and post-COVID. Finally, rolling window analysis ascertained system dependence, centrality, and dynamic networks between green bonds and financial markets where green bond sustained their positive dependence all over the sample period. Green bonds' persistent dependence and centrality enticed several implications for policymakers, regulators, investors, and financial market participants.

Green bonds and other assets: Evidence from extreme risk transmission.

Green bonds (GB) are gaining a prominent role in sustainable development because of their ability to fund environment-friendly projects. This study aims to investigate if investors can benefit from the risk diversification properties of including GB with other assets, particularly within the context of the ongoing COVID-19 pandemic. To do so, we utilize a quantile-connectedness approach to examine a set of GB and traditional assets, i.e., commodities, stocks, and bonds, from 2008 to 2020. We find higher total time-varying risk spillovers during extreme high volatility periods than those with average and low volatility. For pairwise risk spillovers, GB offers more diversification opportunities when volatility is very low. Nevertheless, the diversification benefits increase during the COVID period. The strong bidirectional risk spillovers between GB and conventional bonds imply that GB can be considered a good alternative to traditional bonds while benefiting from their diversification potential, particularly with energy and agriculture. Our findings are useful for investors wishing to implement green diversification portfolio strategies in extreme volatility periods and act as an encouragement to policymakers to establish efficient policies to promote green finance.

Assessment of cadmium and lead tolerance potential of quinoa (Chenopodium quinoa Willd) and its implications for phytoremediation and human health.

Soil contamination with Cd and Pb is a worldwide problem which not only degrades the environment but also poses a serious threat for human and animal health. Phytoremediation of these contaminated soils using halophytic plants like quinoa presents an opportunity to clean the soils and use them for crop production. The current experiment was performed to evaluate the Cd and Pb tolerance potential of quinoa and subsequently its implications for human health. Three weeks old quinoa seedlings were exposed to Cd (30, 60 and 90 mg kg-1) and Pb (50, 100 and 150 mg kg-1) levels along with a control. The results revealed that plant height decreased at highest levels of soil Cd and Pb. Shoot, root and seed dry weight decreased with increasing levels of soil Cd and Pb. Tissue Cd and Pb concentrations increased with increasing levels of Cd and Pb in soil, the highest Cd was found in roots while the lowest in seeds. The highest Pb concentration was found in shoots at low Pb level, while in roots at high level of Pb. Increasing levels of Cd and Pb stimulated the activities of measured antioxidant enzymes and decreased membrane stability index. The health risk assessments of Cd and Pb revealed that hazard quotient was < 1 for both the metals. However, the results of total hazard quotient showed that value was < 1 for Pb and 1.19 for Cd showing potential carcinogenicity. This study demonstrates that quinoa has good phytoremediation potential for Cd and Pb however, the risk of Cd toxicity is challenging for human health.

Genetic Characterization of Highly Pathogenic Avian Influenza A(H5N8) Virus in Pakistani Live Bird Markets Reveals Rapid Diversification of Clade 2.3.4.4b Viruses.

The highly pathogenic (HPAI) avian influenza A(H5N1) viruses have undergone reassortment with multiple non-N1-subtype neuraminidase genes since 2008, leading to the emergence of H5Nx viruses. H5Nx viruses established themselves quickly in birds and disseminated from China to Africa, the Middle East, Europe and North America. Multiple genetic clades have successively evolved through frequent mutations and reassortment, posing a continuous threat to domestic poultry and causing substantial economic losses. Live bird markets are recognized as major sources of avian-to-human infection and for the emergence of zoonotic influenza. In Pakistan, the A(H5N1) virus was first reported in domestic birds in 2007; however, avian influenza surveillance is limited and there is a lack of knowledge on the evolution and transmission of the A(H5) virus in the country. We collected oropharyngeal swabs from domestic poultry and environmental samples from six different live bird markets during 2018-2019. We detected and sequenced HPAI A(H5N8) viruses from two chickens, one quail and one environmental sample in two markets. Temporal phylogenetics indicated that all novel HPAI A(H5N8) viruses belonged to clade 2.3.4.4b, with all eight genes of Pakistan A(H5N8) viruses most closely related to 2017 Saudi Arabia A(H5N8) viruses, which were likely introduced via cross-border transmission from neighboring regions approximately three months prior to virus detection into domestic poultry. Our data further revealed that clade 2.3.4.4b viruses underwent rapid lineage expansion in 2017 and acquired significant amino acid mutations, including mutations associated with increased haemagglutinin affinity to human α-2,6 receptors, prior to the first human A(H5N8) infection in Russian poultry workers in 2020. These results highlight the need for systematic avian influenza surveillance in live bird markets in Pakistan to monitor for potential A(H5Nx) variants that may arise from poultry populations.

Return and volatility transmission between oil price shocks and agricultural commodities.

This paper studies the connectedness between oil price shocks and agricultural commodities. Our sample period ranges from January 2002 to July 2020, covering the three global crises; Global Financial Crisis, the European sovereign debt crisis and Covid-19 pandemic crisis. We employ Granger causality tests, and the static and dynamic connectedness spillover index methodology. We find that the shocks in oil prices are Granger-caused mainly by price changes of grains, live cattle, and wheat, while supply shock granger causes variations mostly in grain prices. We find that, from the point of view of static connectedness, for both, price and volatility spillovers, the livestock is the largest transmitter, while the lean hogs are the major receiver. Our dynamic analysis evidences that connectedness increases during the financial crisis period. Our results are potentially useful for investors, portfolios managers and policy makers.

Empirical analysis of CO2 emissions and sustainable use of energy sources in Pakistan.

Pakistan is experiencing increasing CO2 emissions in contrast with other regions of the world. The country is also facing the problems of low economic growth, energy poverty, and environmental pollution. The objective of the study is to analyze economic growth of Pakistan and obtain some alternate sources of production for sustainable environment. Time series data of Pakistan from 1985 to 2018 is used. In order to estimate direct and substitution effect among energy and non-energy factors on economic growth, translog functional form is used. The presence of multicollinearity among explanatory variables approves to employ ridge regression. Capital per worker has the highest elasticity (0.1531) among all variables followed by consumption of oil (0.0571), natural gas (0.0333), technology (0.0329), and hydroelectricity (0.02). Average output elasticity for oil, natural gas, hydroelectricity, capital per worker, and technology are 0.4474, 0.3127, 0.433, 1.0037, and 0.2309, respectively. Technical progress of variables is ranked as capital per worker, oil consumption, natural gas consumption, hydroelectricity, and technology. Relatively lower but efficient substitution between oil and natural gas provides opportunity to save huge foreign exchange on import of oil. Investment on capital per worker in transport, power, fertilizer, and industrial sectors can reduce the demand of oil and natural gas which would eventually lower carbon dioxide emissions in the country. Increasing 10% investment on capital/worker would mitigate 208.283 million tons of carbon dioxide. Energy inputs are substitutes; therefore, mega hydropower projects and small renewable projects may be launched to cope with energy poverty and environmentally sustainable challenges.

COVID-19 and time-frequency connectedness between green and conventional financial markets.

Against the backdrop of the exponentially growing trend in green finance investments and the calls for green recovery in the post-COVID world, this study presents the time-frequency connectedness between green and conventional financial markets by using the spillover models of Diebold and Yilmaz (2012) and Baruník and Krehlík (2018). Covering a sample period from January 01, 2008, to July 31, 2020, we aim to explore the dynamics of connectedness between conventional and green investments in fixed income, equity, and energy markets. Additionally, we determine the role of market-wide uncertainty in altering the connectedness structure by performing a subsample analysis for the ongoing COVID-19 pandemic crisis period. Our results show that competing energy investments are not connected, and there is only one-way spillovers from the conventional bonds in the fixed-income investments. Additionally, we observe a low (high) intergroup connectedness for conventional (green) investments. Moreover, the frequency-based analysis shows that connectedness between these competing markets is more pronounced during the short-run. The subsample analysis for the pandemic crisis period shows similar results except for the disconnection between bond markets in the short-run frequency. Our time-varying analysis shows peaks and troughs in the connectedness between climate-friendly and conventional investments that suggest different global events such as the Eurozone Debt Crisis and Shale Oil Revolution drives the association between alternate investments. Similarly, we observe an enhanced connectedness during the recent COVID-19 period, suggesting that financial stability would be a significant factor in determining the smooth transition to green investments.

In-Vitro Assessment Of The Therapeutic Potential Of Polymyxins And Tigecycline Against Multidrugresistant Acinetobacter Isolates From Infected Wounds.

BACKGROUND: The incidence of multidrug-resistant (MDR), extreme drug resistant (XDR), and pan drug-resistant (PDR) Acinetobacter are increasing throughout the world. The therapeutic management and control of Acinetobacter are difficult due to the emergence of drug resistance and its enduring capacity to survive in the environment. The present study was designed to appraise the efficacy of Polymyxins and Tigecycline against multidrugresistant Acinetobacter isolates from surgical and burn wounds. METHODS: During the study, the specimens were collected from various types of wounds from inpatients and outpatients of the tertiary care hospitals of Lahore, Pakistan in 2017 and 2018. The bacterial pathogens were isolated and identified using standard microbiological procedures and molecular confirmation of Acinetobacter species was examined by PCR using specific primers. The antibiotic susceptibility profiling of Acinetobacter isolates was studied against 18 antibiotics as per Clinical and Laboratory Standards Institute (CLSI) guidelines. RESULTS: The Acinetobacter isolates demonstrated extreme resistance especially to ampicillin/sulbactam, piperacillin/tazobactam, cephalosporins, carbapenems, fluoroquinolones, and aminoglycosides. However, the colistin, polymyxin, and tigecycline remained the most effective antimicrobial agents against Acinetobacter isolates. CONCLUSIONS: The results highlight the extent of drug resistance and therapeutic potential of Polymyxins and Tigecycline for wound infections caused by MDR and XDR Acinetobacter species. The wiser use of antimicrobials, incessant surveillance of antimicrobial resistance, and stringent adherence to infection control guidelines are critical to reducing major outbreaks in the future.

Quantification and risk assessment of heavy metal build-up in soil-plant system after irrigation with untreated city wastewater in Vehari, Pakistan.

In peri-urban areas of district Vehari, farmers are using untreated city wastewater for crop irrigation owing to the scarcity of good-quality irrigation water. This practice may pose severe environmental and health issues to local inhabitants attributed to the high levels of potentially toxic metals in wastewater. The present study evaluated the potential impacts of wastewater irrigation on metals (Cd, Cr, Cu, Fe, Ni, Mn, Pb and Zn) build-up in the soil-plant continuum and associated health risks. In this study, wastewater (n = 17), soil (n = 108) and plant (n = 65) samples were collected from 15 peri-urban sites of three tehsils of district Vehari. Results showed that the mean concentration (mg/L) of Cd (0.02), Mn (0.25) and Fe (1.57) in wastewater samples was higher than their respective threshold values. Similarly, Cd, Mn and Fe concentration in soil was beyond the permissible limits of agricultural soil receiving wastewater irrigation. However, plants showed high accumulation of Pb, Cr and Fe than their respective limits depending on the vegetable/crop species. The health risk parameters showed that Pb and Cd are the major toxic chemical substances to human health, and the daily intake of crop plants can pose a potential health threat due to wastewater-irrigated crop consumption. Results highlighted the necessity of wastewater pretreatment to avoid the soil and vegetable contamination by wastewater irrigation and to reduce the associated health risks.