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This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

Background: A range of local social and environmental factors has an impact on farmers' views of climate change and choices on the use of coping mechanisms. This study examines the factors that are limiting farmers' perceptions of climate change and their coping mechanisms in Gimbi district, Western Ethiopia.

Methods: A household survey and focus group discussion were employed to collect relevant data. A total of 402 randomly selected households and six focus group discussions containing 72 participants were used to gather data. Binary logit models were used to analyze the collected data.

Results: Farmers noted that some of the signs of climate change included increasing temperature, erratic rainfall, late onset of rainfall, and early cessation of rainfall. We discovered that there are three distinct sets of climate adaption strategies used by farmers: crop management, soil and water conservation and intensive farm management. The primary determinants of farmers' perceptions of climate change and adaptation techniques were household head age, education, soil fertility, market access, and agricultural training. Age, education, and soil fertility level were the characteristics that significantly impacted farmers' perspectives and coping mechanisms among the primary drivers evaluated in the area. Use of agroforestry, shifting planting dates, and fertilizer application were all essential farming practices used as climate adaptation measures.

Conclusions: Both socioeconomic and environmental factors have found to affect farmers' perceptions of climate change in the area. The existing socioeconomic and environmental factors, in turn, affect their choice of strategies to adapt to climate change. When implementing climate change adaption strategies, it is critical to assess farmers' level of awareness of climate change and their coping strategies, as well as the factors limiting their ability to adapt to climate change.

The purpose of this study results and recommendations will have a paramount significance for policymakers, policy advocates, development planners and practitioners who may be in need of such information for reconsideration, evaluation and inclusion into their respective development and humanitarian programming and operational strategies. Above all, the study result has further provided the local community with viable adaptation strategies to climate-induced changes in the study area.

This study was conducted to measure the livelihood vulnerability of Borana pastoralists to climate change and variability in southern Ethiopia. Pastoralists’ households were sampled using multistage sampling techniques. A total of 27 socio-economic and biophysical indicators were used to reflect vulnerability components: adaptive capacity, exposure and sensitivity. Principal component analysis was used to develop weights for indicators and to produce livelihood vulnerability index to classify households according to their level of vulnerability. Ordinal logistic regression was used to identify the determinants of vulnerability to climate-induced stresses.

The results showed that 24.4% of households were highly vulnerable, 60.3% were moderately vulnerable and 15.3% of households were less vulnerable to climate-induced stresses. Factor estimates of the logistic model further revealed that early warning information, bush encroachment, coping strategy, temperature, drought frequency, provision of humanitarian services and food shortage during the normal season of the year have a significant influence on vulnerability in the study area.

The study’s results and recommendations will be of great significance to policymakers, development planners, and practitioners who require such information for reconsideration, evaluation, and inclusion in their respective development and humanitarian program and operational strategies. Most importantly, the study’s findings have provided the local community with practical adaptation strategies to climate-induced changes in the study area.

The study explored pastoralist perception of climate change and variability and measured the livelihood vulnerability of pastoralists’ households to climate change and variability and finally investigated viable adaptation and coping strategies in the study area.

To proactively draw efficient maintenance plans, road agencies should be able to forecast main road distress parameters, such as cracking, rutting, deflection and International Roughness Index (IRI). Nonetheless, the behavior of those parameters throughout pavement life cycles is associated with high uncertainty, resulting from various interrelated factors that fluctuate over time. This study aims to propose the use of dynamic Bayesian belief networks for the development of time-series prediction models to probabilistically forecast road distress parameters.

While Bayesian belief network (BBN) has the merit of capturing uncertainty associated with variables in a domain, dynamic BBNs, in particular, are deemed ideal for forecasting road distress over time due to its Markovian and invariant transition probability properties. Four dynamic BBN models are developed to represent rutting, deflection, cracking and IRI, using pavement data collected from 32 major road sections in the United Arab Emirates between 2013 and 2019. Those models are based on several factors affecting pavement deterioration, which are classified into three categories traffic factors, environmental factors and road-specific factors.

The four developed performance prediction models achieved an overall precision and reliability rate of over 80%.

The proposed approach provides flexibility to illustrate road conditions under various scenarios, which is beneficial for pavement maintainers in obtaining a realistic representation of expected future road conditions, where maintenance efforts could be prioritized and optimized.

The purpose of this paper was to examine smallholder farmers’ perceptions of climate change risks, adaptation responses and the links between adaptation strategies and perceived/experienced climate change risks in South Gondar, Ethiopia.

This paper used a convergent mixed methods design, which enables us to concurrently collect quantitative and qualitative data. Survey data was collected from 352 households, stratified into Lay Gayint 138 (39%), Tach Gayint 117 (33%) and Simada district 97 (28%). A four-point Likert scale was used to produce a standardised risk perception index for 14 climate events. Moreover, using a one-way analysis of variance, statistical differences in selecting adaptation strategies between the three districts were measured. A post hoc analysis was also carried out to identify the source of the variation. The findings of this paper are supplemented by qualitative data gathered through focus group discussions and key informant interviews of households who were chosen at random.

The standardised climate change risk perception index suggests that persistent drought, delayed onset of rainfall, early termination of rainfall and food insecurity were the major potentially dangerous climate change risks perceived by households in the study area. In response to climate change risks, households used several adaptation strategies such as adjusting crop planting dates, crop diversification, terracing, tree planting, cultivating drought-tolerant crop varieties and off-farm activities. A Tukey’s post hoc test revealed a significant difference in off-farm activities, crop diversification and planting drought-tolerant crop types among the adaptation strategies in the study area between Lay Gayint and Simada districts (p < 0.05). This difference reconfirms that adaptation strategies are location-specific.

Although many studies are available on coping and adaptation strategies to climate change, this paper is one of the few studies focusing on the linkages between climate change risk perceptions and adaptation responses of households in the study area. The findings of this paper could be helpful for policymakers and development practitioners in designing locally specific, actual adaptation options that shape adaptation to recent and future climate change risks.

This study aims to examine the phenomenon of climate variability and its implications for pastoralists and agro-pastoralists food security in Amibara and Awash Fentale districts of the Afar region, Ethiopia.

The study relied on meteorological records of temperature and rainfall in the study area between 1988 and 2018. Besides, literature on the topic was reviewed to make caveats on the literal picture that comes from quantitative data, and that is the contribution of this study to the existing debate on climate change and variability. The spatiotemporal trend was determined using the Mann–Kendall test and Sen’s slope estimator, while variability was analyzed using the coefficient of variation and standardized anomaly index, and standardized precipitation index/standardized precipitation evapotranspiration index were applied to determine the drought frequency and severity.

The result reveals that the mean seasonal rainfall varies from 111.34 mm to 518.74 mm. Although the maximum and minimum rainfall occurred in the summer and winter seasons, respectively, there has been a decrease in seasonal and annual at the rate of 2.51 mm per season and 4.12 mm per year, respectively. The study sites have been experiencing highly seasonal rainfall variability. The drought analysis result confirms that a total of nine agricultural droughts ranging from moderate to extreme years were observed. Overall, the seasonal and annual rainfall of the Amibara and Awash Fentale districts showed a decreasing trend with highly temporal variations of rainfall and ever-rising temperatures, and frequent drought events means the climate situation of the area could adversely affect pastoral and agro-pastoral households’ food security. However, analysis of data from secondary sources reveals that analyzing precipitation just based on the meteorological records of the study area would be misleading. That explains why flooding, rather than drought, is becoming the main source of catastrophe to pastoral and agro-pastoral livelihoods.

The analysis of temperature and rainfall dynamics in the Afar region, hence the inception of all development interventions, must take the hydrological impact of the neighboring regions which appears to be useful direction to future researchers.

The research is originally conducted using meteorological and existing literature, and hence, it is original. In this research, we utilized a standardized and appropriate methodology, resulting in insights that augment the existing body of knowledge within the field. These insights serve to advance scholarly discourse on the subject matter.

As climate change impacts residential life, people typically use heating or cooling appliances to deal with varying outside temperatures, bringing extra electricity demand and living costs. Water is more cost-effective than electricity and could provide the same body utility, which may be an alternative choice to smooth electricity consumption fluctuation and provide living cost incentives. Therefore, this study aims to identify the substitute effect of water on the relationship between climate change and residential electricity consumption.

This study identifies the substitute effect of water and potential heterogeneity using panel data from 295 cities in China over the period 2004–2019. The quantile regression and the partially linear functional coefficient model in this study could reduce the risks of model misspecification and enable detailed identification of the substitution mechanism, which is in line with reality and precisely determines the heterogeneity at different consumption levels.

The results indicate that residential water consumption can weaken the impact of cooling demand on residential electricity consumption, especially in low-income regions. Moreover, residents exhibited adaptive asymmetric behaviors. As the electricity consumption level increased, the substitute effects gradually get strong. The substitute effects gradually strengthened when residential water consumption per capita exceeds 16.44 tons as the meeting of the basic life guarantee.

This study identifies the substitution role of water and heterogeneous behaviors in the residential sector in China. These findings augment the existing literature and could aid policymakers, investors and residents regarding climate issues, risk management and budget management.

Climate change is an undeniable reality that threatens people’s livelihoods. Flooding and saltwater intrusion, along with the rising sea levels, are affecting agricultural and aquaculture livelihoods in Myanmar’s coastal areas. Although climate change adaptation is gaining popularity as a resilience strategy to cope with the negative effects of climate change, both agriculture- and aquaculture-farmers are more often deterred from implementing climate change adaptation strategies due to practical availability and socioeconomic barriers to adaptation. This study aims to evaluate the barriers and factors that influence farm household’ choice of climate change adaptation measures.

This study was conducted with 599 farm households (484 rice-farmers and 115 fish farmers) based in the coastal areas of Myanmar during 2021–2022 to explore the farmer’s choice of climate change adaptation measures and the determining factors. The multinomial logit regression (MLR) model was used to examine the factors influencing the farmers’ choice of climate change adaptation strategies.

The study found out that farm households use a variety of adaptation methods at the farm level, with building embankment strategy (23.4%) in agriculture and net-fencing measure (33.9%) in fish farming being the most popular adaptation strategies. Farmers’ decisions to adopt climate change adaptation strategies are influenced by factors such as distance to market, education level of the household head, remittance income and the availability of early warning information, among others. The study also discovered that COVID-19 has had an impact on the employment opportunities of household members and the income from farming as well had a consequential effect on the adoption of climate change adaptation measures. Furthermore, lack of credit (42.4%), labor shortage (52.8%), pest and disease infestation (58.9%), high input costs (81%) and lower agricultural product prices (73%) were identified as major barriers to the adoption of climate change adaptation measures by both agriculture and aquaculture farm households.

This study demonstrates that the COVID-19 pandemic and farm-level barriers are the major factors influencing farm households’ choice of climate change adaptation measures, and that removing practical farm-level barriers and encouraging the adoption of adaptation techniques as potential COVID-19 recovery actions are required. This study also highlighted that the adaptive capacity of agriculture and aquaculture farm households should be strengthened through formal and informal training programs, awareness raising, the exchange of early warning information and the development of proper credit scheme programs.

This study aimed to characterize the concentrations of indoor pollutants (such as carbon dioxide (CO₂), ozone (O₃), nitrogen dioxide (NO₂) and sulfur dioxide (SO₂), as well as particulate matter (PM) (PM₁, PM_2.5 and PM₁₀) in Akure, Nigeria, as well as the relationship between the parameters’ concentrations.

The evaluation, which lasted four months, used a low-cost air sensor that was positioned two meters above the ground. All sensor procedures were correctly carried out.

CO₂ (430.34 ppm), NO₂ (93.31 ppb), O₃ (19.94 ppb), SO₂ (40.87 ppb), PM₁ (29.31 µg/m3), PM_2.5 (43.56 µg/m³), PM₁₀ (50.70 µg/m³), temperature (32.4°C) and relative humidity (50.53%) were the average values obtained. The Pearson correlation depicted the relationships between the pollutants and weather factors. With the exception of April, which had significant SO₂ (18%) and low PM₁₀ (49%) contributions, NO₂ and PM₁₀ were the most common pollutants in all of the months. The mean air quality index (AQI) for NO₂ indicated that the AQI was “moderate” (51–100). In contrast to SO₂, whose AQI ranged from “moderate” to “very unhealthy,” O₃'s AQI ranged from “good” (50) to “unhealthy” (151–200). Since PM₁, PM_2.5 and PM₁₀ made up the majority of PC1’s contribution, both PM_2.5 and PM₁₀ were deemed “hazardous.”

The practical implication of indoor air pollution is long-term health effects, including heart disease, lung cancer and respiratory diseases such as emphysema. Indoor air pollution can also cause long-term damage to people’s nerves, brain, kidneys, liver and other organs.

Lack of literature in terms of indoor air quality (IAQ) in Akure, Ondo State. With this work, the information obtained will assist all stakeholders in policy formulation and implementation. Again, the low-cost sensor used is new to this part of the world.

The study examined the influence of humanitarian organizations’ culture and financial service providers’ technology readiness on the usage of digital cash-based assistance by humanitarian organizations, the influence of Humanitarian Organization Culture on Financial providers’ technology readiness and the mediating role of financial service providers’ technology readiness on the relationship between the culture in humanitarian organizations and their usage of digital cash-based assistance.

A quantitative cross-sectional survey design was used. The target population consisted of humanitarian organizations that were members of the Uganda Cash Consortium (UCC). The research hypotheses were tested using SMART PLS version 4.

The culture in humanitarian organizations and financial service providers’ technology readiness positively influences the usage of digital cash-based assistance by humanitarian organizations during humanitarian crises, and humanitarian organizations’ culture positively influences financial service providers’ technology readiness. Financial service providers’ technology readiness fully mediates the relationship between the culture of humanitarian organizations and the usage of digital cash-based assistance by humanitarian organizations during humanitarian crises.

The study mainly focuses on culture in humanitarian organizations and financial service providers’ technology readiness when examining the usage of digital cash-based assistance during humanitarian crises. Further, financial service providers’ technology readiness is examined using a humanitarian organization, financial service provider and beneficiary/persons of concern’s point of view rather than the government’s point of view.

Research examining determinants for digital cash-based assistance usage in humanitarian crises is scarce. Further, empirical research examining the influence of the humanitarian organizations’ culture and financial service providers’ technology readiness in promoting the usage of digital cash-based assistance in humanitarian crises, the impact of humanitarian organizations’ culture on financial service providers’ technology readiness and the mediating role of financial service providers’ technology readiness on the relationship between the culture of humanitarian organizations and usage of digital cash-based assistance in humanitarian crises are non-existent. The majority of research and grey literature focuses on how digital cash-based transfers can be used to enhance financial inclusion in refugee contexts.