RESUMO
For decades, rivers have been used for transporting pollutants loaded with heavy metals (HMs) causing severe pollution in downstream. The current study aimed to review the levels and sources of 10 HMs, viz. As, Pb, Cd, Cr, Fe, Mn, Cu, Co, Ni, and Zn in the surface water of the rivers in Bangladesh. The PRISMA criteria were used to conduct a systematic review of the available literature published between 2001 and 2020, and thus a total of 55 documents were finally selected for review. The mean concentration of each HM exceeding the threshold limits as per World Health Organization (WHO), the United States Environmental Protection Agency (USEPA), and Department of Environment (DoE), Bangladesh standards were higher in the last decade (2011-2020) than in the previous one (2001-2010). Most HM concentrations in water were found above the threshold limits in three divisions (Dhaka, Rajshahi, and Chattogram). The Buriganga River in Dhaka has been the top polluted river in Bangladesh. Among the 10 HMs, six metals (As, Pb, Cd, Cr, Fe, and Mn) exceeded the limit set by WHO, USEPA, and DoE in all three seasons, where mean values of most of the HMs were found to be the highest in the summer season. Statistical analyses identified possible sources of HMs such as natural weathering, electroplating, fertilizers and pesticides, mining and manufacturing, textiles, coal mining and burning, batteries, and paint industries. Strong legislations and regulations, awareness programs, continuous monitoring, and comprehensive research are urgently needed to control riverine HMs pollution in Bangladesh.
RESUMO
Background and Aims: Two main problems the globe currently facing are migration and weather variation. Weather change has a significant impact on the agricultural industry, which affects the majority of poor people. There is a dearth of adequate methodological documentation when examining the relationship between weather variation, agricultural output, and migration. We aimed to identify methodological reporting difficulties by reviewing the quantitative literature on weather-related migration through agricultural channels. Methods: A systematic evaluation was conducted using papers published between January 2010 and June 2022, indexed in the SCOPUS, PUBMED, and Google Scholar databases. Using inclusion/exclusion criteria, we selected 22 original research articles out of 18,929 distinct articles for review, in accordance with the PRISMA guidelines. We extracted data from each study to understand how various concepts, research designs, and investigative techniques influence our understanding of migration patterns related to weather in the agricultural sector. Results: The majority (64%) of the study's data consisted of time series data. In 50% of the studies, secondary data were used. Additionally, 55% of these studies did not state the sample size. In 40% of the studies, model assumptions were fully adhered to, whereas in 36% of the studies, they were not followed at all. The majority of the articles used the Ordinary Least Squares technique, while about 41% applied the Two-Stage Least Squares technique. Various tests were conducted across these studies, such as robustness checks (59.1%), endogeneity tests (31.8%), omitted variable bias tests (22.7%), sensitivity analyses (22.7%), and weak instrument tests (13.6%), to name a few. In the research we selected, the methodology section had various shortcomings and lacked organization. Furthermore, the justifications for deviations from model assumptions were unclear, potentially affecting the study outcomes. Conclusion: This study has important indications for researchers in studying climatic (weather) migration through agricultural channels besides for policymakers by giving a thorough review of the methods and techniques.