Spatial variance and assessment of nitrogen dioxide pollution in major cities of Pakistan along N5-Highway

This paper discusses the findings of the first car MAX-DOAS (multi-axis differential optical absorption spectroscopy) field campaign (300 km long) along the National Highway-05 (N5-Highway) of Pakistan conducted on 13 and 14 November, 2012. The main objective of the field campaign was to assess the spatial distribution of tropospheric nitrogen dioxide (NO₂) columns and corresponding concentrations along the N5-Highway from Islamabad to Lahore. Source identification of NO₂ revealed that the concentrations were higher within major cities along the highway. The highest NO₂ vertical column densities (NO₂ VCDs) were found around two major cities of Rawalpindi and Lahore. This study also presents a comparison of NO₂ VCDs measured by the ozone monitoring instrument (OMI) and car MAX-DOAS observations. The comparison revealed similar spatial distribution of the NO₂ columns with both car MAX-DOAS and satellite observations, but the car MAX-DOAS observations show much more spatial details. Maximum NO₂ VCD retrieved from car MAX-DOAS observations was up to an order of magnitude larger than the OMI observations in urban areas.     

Reverse logistics in the Chinese auto-parts firms: implementation framework development through multiple case studies

In recent years, the implementation of reverse logistics (RL) in automobile manufacturing has drawn extensive interest from the Chinese government that has launched relevant take-back and environmental regulations and pilot projects. This study focuses on RL implementation issues in Chinese auto-parts manufacturing sector. Based on comprehensive literature review and multiple case studies in the Chinese auto-parts firms, this paper proposes a conceptual RL framework and highlights the major implementation issues. The purpose of this paper is to draw an overall picture of RL in the Chinese context, highlighting implementation issues in the auto-parts sector. Our study suggests that Chinese RL implementation requires close government monitoring mechanism and incentives, top management commitment within firms, technology and human capabilities support.     

Assessing the nexus between COVID-19 pandemic–driven economic crisis and economic policy: lesson learned and challenges

Environmental Science and Pollution Research - This study examines China’s budgetary policy during the COVID-19 pandemic as a result of China’s insufficient ability to deal with a new...     

Fresh evidence on connectedness between prominent markets during COVID-19 pandemic

Environmental Science and Pollution Research - Various empirical studies have examined the nexus between financial markets, but this study focused on the comovement among prominent markets. Our...     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Geochemical fractionation and spectroscopic fingerprinting for evaluation of the environmental transformation of potentially toxic metal(oid)s in surface–subsurface soils

Environmental Geochemistry and Health - The contamination of soil by toxic metal(oid)s has emerged as a major concern worldwide, particularly in developing countries. A metals behavior in the soil...     

Cattle egrets as a biosentinels of persistent organic pollutants exposure

We investigated selected chlorinated pollutants (β-HCH, γ-HCH, DDDs, DDEs, o,p′-DDT, p,p′-DDT, heptachlor, aldrin, dieldrin, and endrin) in the Lahore and the Sialkot districts of Pakistan, using eggs of cattle egret (Bubulcus ibis) collected during May and June 2007. The pollutant with highest level and frequency was ΣDDT, followed by β-HCH, γ-HCH, heptachlor, aldrin, dieldrin, and endrin in descending order. The concentration(s) were significantly higher in Sialkot heronry for all the pollutants (except p,p′-DDT) than in Lahore. The values for DDTs, β-HCH, γ-HCH, and heptachlor were significantly higher (p < 0.05) in the egg(s) than in sediment(s) and in the chicks’ diet, due to biomagnification. Among DDTs analogues, p,p′-DDD was the major contaminant with >60 % of total DDT burden, reflecting the widespread aged as well as recent use of DDT as well as anaerobic degradation (DDD/DDE > 1 in many cases) in the nearby paddy soils. In few samples, p,p′-DDT/(DDD + DDE) > 0.5 suggested the recent emission patterns from surrounding contaminated areas of demolished DDT units and obsolete pesticide stores. The higher levels of HCHs (i.e., β-HCH) in the samples collected from Sialkot indicate exposure from long-term agricultural use. Overall, concentrations of all studied POPs were less than the threshold levels known to affect reproduction. Nevertheless, total DDTs and/or HCHs burdens in some eggs contained concentrations of greater than what would educe adverse effects on birds. This is among few studies on OCPs exposure to avian species, which provide the evidence of Pakistan’s contribution toward the Global POPs emission.     

Rapid liquid chromatographic analysis of Metoclopramide in pharmaceutical preparations

A sensitive, accurate and reproducible method for the analysis of metoclopramide, a gastrointestinal drug, has been described. An isocratic HPLC elution method was employed which requires about 10 minutes to be performed. The concentration of metoclopramide hydrochloride preparations was found to be 95.1 ±0.3% and 94.21 ±0.25% in tablet and injection formulations, respectively.     

Sol-gel immobilisation of methyl parathion degrading bacteria isolated from agricultural areas of Pakistan

The following areas are discussed in this paper: immobilisation of bacterial consortium in sol-gel; methyl parathion degradation and bioremediation applications; evaluation of indigenous bacterial isolates of contaminated soils. Bacterial strains were isolated from agricultural areas of Pakistan which were contaminated with methyl parathion. A bacterial consortium of seven (out of 64) Enterobacteriaceae isolates including Citrobacter, Enterobacter and Proteus vulgaris capable of degrading methyl parathion (enzyme activity ranging 410–675 mU mL^?1 for individual isolates and 982 mU/mL for consortium) was selected and subsequently immobilised in tetraethyl orthosilicate (TEOS) and sodium-silicate-based sol-gel matrices. Cell viability of suspended and immobilised bacterial consortium was monitored using a minimal salt medium supplemented with methyl parathion. The results indicate that sol-gel immobilisation can be helpful to increase the shelf life of methyl parathion degrading bacterial strains along with preservation of biological activity for bioremediation applications in field.