Water resources in the Chia lagoon in Malawi experience a possible threat to sustainability. Communities are seeking alternatives to improve water quality in the lagoon. This study quantified the communities’ willingness-to-pay (WTP) and their influencing factors while using contingent valuation (CV) techniques. A wide range of data collection procedures, including focus group discussions, key informant interviews, field observation, and CV survey, were employed. A sample of 300 households was randomly selected. The CV results showed that 57.4% of the households were willing to pay. The monthly individual aggregate WTP amount ranged from MK696.83 (US$0.95) to MK81697 (US$111.38), and on average MK7870.45 (US$10.73), generating aggregate annual values ranging from MK6, 689,568 (US$9126.29) to MK784, 294,080 (US$1,069,978), and on average MK75,556,320 (US$103,078) (ceteris paribus). Logistic regression model demonstrated a significant (p < 0.01 or p < 0.05) relationship between demographic (gender, age, literacy level), social-economic (land ownership, main agriculture water source, and income), and institutional (civic education and social network, extension, institutional trust, household socio trust) factors and WTP. The findings from this study provide significant clues for further research and baseline information for local government and communities in the development of more effective and holistic approaches for improving water quality in natural ecosystems.

This review gives insights into the levels of metals in urban dust, their determination methods, and risk assessment. Urban dust harbors a number of pollutants, including heavy metals. There are various methods used for the sampling of urban dust for heavy-metal analysis and source-apportionment purposes, with the predominant one being the use of plastic sampling materials to avoid prior contamination. There are also various methods for the determination of metals, which include: atomic absorption spectroscopy (AAS) and inductively coupled plasma-mass spectrometry (ICP-MS), among others. Studies have shown that pollutants in urban dust are mainly derived from industrial activities and coal combustion, whereas traffic emissions are also an important, but not a predominant source of pollution. The varying particle-size distribution of urban dust and its large surface area makes it easier for the deposition and transport of heavy metals. Risk-assessment studies have shown that metals in urban dust could cause such problems as human pulmonary toxicity and reduction of invertebrate populations. The risk levels seem to be higher in children than adults, as some studies have shown. It is therefore important that studies on metals in urban dust should always incorporate risk assessment as one of the main issues.

This study employed a deductive research approach and a survey strategy to assess risk perception and its influencing factors among construction workers in Malawi. Three specific construction hazards and their associated risks were selected. The hazards were “working at height (WAH)” “manual handling of loads (MHL)” and “heavy workload or intense pressure to be more productive (HWP).” The study engaged multistage sampling of 376 subjects. Univariate analysis, factor analysis and multiple linear regressions were performed in order to determine the main influencing factors among the independent variables. The study established that workers were aware of risks posed by their work. The majority perceived the risk associated with WAH, MHL and HWP as very high (62.7%, =8.80 ± 1.95); (48.5%, =8.10 ± 2.38); (57.9%, =8.49 ± 2.22) respectively. The study identified six factors as variables that showed a significant effect on workers’ perception of risk (p < 0.05). These factors were: “dreaded factor,” “avoidability and controllability,” “expert knowledge,” “personal knowledge,” “education level,” and “age”. It is concluded that contractors in the Malawian construction industry should integrate analysis of behaviors and risk perception of the workers and other players to guide the identification of better health and safety interventions at their worksites.

Pesticides pose a significant risk to humans and the environment. This paper analyzes the measures used to manage pesticides in Malawi. Malawi’s regulatory authority of pesticides, the Pesticides Control Board (PCB), faces a number of challenges including lack of facilities for analyzing pesticides and inadequate personnel to conduct risk assessment of pesticides. The PCB needs to provide access to information and opportunities among the public to make contributions regarding requirements, processes and policies for assessing pesticide risk and efficacy. There is also a need to enhance the capacity of PCB to assess pesticide poisoning in workers, monitor pesticide residues in food and environmental contamination, as well as to control the illegal importation and sale of pesticides. Just like in other countries such as South Africa, India and Sri Lanka, Malawi urgently needs to implement measures that can restrict the importation, production, sale and use of very toxic pesticides. Malawi also needs to develop measures for the effective management of pesticide waste containers as well as obsolete pesticides, where potential solutions include reducing the purchase of (unneeded) pesticides, treatment of obsolete pesticides in high-temperature cement kilns, as well as requesting pesticide dealers to adopt life-cycle management of their products.

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E₂), coefficient of determination (R²), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R², and E₂. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

Inland freshwater shallow lake ecosystem degradation is indistinctly intertwined with human-induced factors and climate variability. Changes in climate and human-induced factors significantly influence the state of lake ecosystems. This study provides evidence of the driver, pressure, state, impact, and response (DPSIR) indicators for freshwater lake ecosystem dynamics, taking Lake Malombe in Malawi as a case study. We used the DPSIR framework and Tobit model to achieve the study’s objectives. The study’s findings indicate that top-down processes gradually erode Lake Malombe’s ecosystem state. The lake resilience is falling away from its natural state due to increasing rates of drivers, pressures, and impacts, indicating the lake ecosystem’s deterioration. The study shows that demographic, socio–economic, climatic drivers, pressures, state, and responses significantly (p < 0.05) influenced the lake ecosystem’s resilience. The study suggests that substantial freshwater ecosystem management under the current scenario requires a long-term, robust, and sustainable management plan. The findings from this study provide a roadmap for short-term and long-term practical policy-focused responses, particularly in implementing a freshwater ecosystem restoration programs in Malawi and Africa more broadly.