• Energy Research

More than three-quarters of the world's total cultivated land is under rainfed farming, producing almost 70% of total food. Most food production comes from developing and least favored nations. Pakistan, a developing country with an agro-based economy, is facing severe threats from climate change. Rainfed agriculture, especially wheat farming, is highly susceptible due to its heavy dependency on precipitation, one of the most important climatic parameters. Wheat is the main food crop, as well as a major source of calorific intake, for millions of people in Pakistan. This study aims to quantify the impacts of climate variability on mean yield levels and yield variability of wheat crop in the rainfed zone of Pakistan. Multistage random sampling technique is used for primary data collection from 400 rainfed wheat farmers during the 2016-17 crop season. The study uses primary data on crop input-output, management, socioeconomic, institutional, and historical climatic data (1980-2017). The data are analyzed employing the Just and Pope (J-P) stochastic production function approach with linear and non-linear functional forms. The results reveal that temperature rise negatively affects observed wheat mean yields, while cumulative precipitation positively affected it. Further, input market access, seed rate, and cumulative precipitation also cause variability in yield levels, leading to yield instability. Further, farm elevation influences wheat mean yield positively while input market access influences it negatively. The findings of the study have important implications for climate resilient wheat farming. Timely and tailor-made adaptations need to be undertaken in the rainfed wheat farming systems of Pakistan. Creating awareness among farmers about the optimal use of agronomic inputs under changing climatic conditions could be an effective adaptation strategy that improves yields and copes with yield instability.

Climate change is a severe threat to the agricultural sector in general and to rainfed farming in particular. The aim of this study was to investigate the factors that can potentially affect the adaptation process against climate change. This study focused on wheat farmers and farming systems in the rainfed agroecological zone of Pakistan. Farmers’ data related to climate change fatalism, the availability of climate-specific extension services, socioeconomic and institutional variables, and farm characteristics were collected. A logit model to assess farmers’ decisions to adopt an adaptation measure and a multinomial logit model to assess their choice of various adaptation measures were used. The results showed that fatalistic farmers were unlikely to implement climate change adaptation measures. The variables related to the climate-specific extension services, including farmers’ participation in training on climate-resilient crop farming and the availability of mobile communication-based advisory services, had highly significant and positive impacts on farmers’ decisions and their choice of adaptation measures. Input market access and tractor ownership also had positive and significant impacts on farmers’ decisions to adapt and their choice of adaptation measures. This study highlights the need to improve rainfed-wheat farmers’ education levels to change their fatalistic attitudes towards climate change. Furthermore, government action is needed to provide climate-specific extension services to ensure sustainable production levels that will ultimately lead to food and livelihood security under a changing climate.

Scientific evidence suggests that there is room for eradicating poverty and hunger by increasing food production through the adoption of modern agricultural practices by farmers. This study aimed, first, to explore the relationship between the farmers’ awareness and adoption of improved wheat varieties. Second, it aimed to find the key factors that govern the farmers’ awareness and adoption of extension-recommended innovations in the rainfed cropping system of the Khyber Pakhtunkhwa, Pakistan. Data were collected from 395 respondents. A binary logit model was used to analyze the effect of the farmers’ socioeconomic and farm-specific characteristics on their awareness and adoption of the extension-suggested wheat varieties. Moreover, qualitative data from 40 key informants were collected for in-depth analysis. The results show a strong association between the farmers’ awareness of a technology (improved wheat varieties) and its adoption. The results of the logit model show that their extension contacts, income from agriculture, and access to credit positively affected the farmers’ awareness, whereas their education and household sizes negatively affected their awareness. Moreover, the factors that positively influenced the farmers’ decision to adopt the technology included the extension contact, the confidence in the extension, the risk-bearing attitude, and the credit access, whereas the household size and education negatively affected it. The results of the key informant interviews reveal that the high incidence of poverty, the low soil fertility, the farmers’ inability to make effective decisions, the lack of accurate weather predictability in the rainfed farming system, the lack of government interest, and the asymmetric information in the inputs markets contributed to the farmers’ low levels of awareness and to their poor adoption of improved agricultural technologies. These results indicate that any intervention aimed at the awareness and adoption by farmers of improved technologies, such as new wheat varieties, should recognize the heterogeneity in the farmers’ socioeconomic and farm-specific characteristics.

Using survey information of 150 randomly selected households across 21 villages of the forest-rich district of Swat, Pakistan, this study assessed households’ decision-making behaviors in depending on income from nearby forested land using socio-economic attributes. The evidence from the study may aid in making the existing policies be better targeted toward families that depend on the forest for income. Descriptive statistics and econometric techniques such as logit and tobit were used to analyze the data. Respondent households obtained the highest share of their income from off-farm activities (37%) and least from forest activities (16%). Fuelwood constitutes the biggest share (66%) of forest income, followed by medical plants (20%) and fodder (13%). We found that households with more physical assets, more family members working in off-farm jobs, and households earning more income from off-farm jobs were significantly and negatively associated with households’ decision to depend on forest income and total income obtained. We also found that households with less distance to the market and membership to joint forest management committees (JFMCs) were significantly and negatively associated with households’ total income obtained. However, household size was significantly and positively related to households’ decision of forest dependency. The study recommends the creation of off-farm opportunities and inclusion of local people in the management of forests through establishment of JFMCs, particularly for large and poor families.

Air pollution is among the major causes of death and disease all around the globe. The prime impact of ambient air pollution is on the lungs through the respiratory system. This study aims to estimate the health cost due to air pollution from a Sugar Mill in the Mardan district of Khyber Pakhtunkhwa, Pakistan. To determine the impact of pollution on respiratory illness, primary data were collected from 1141 individuals from 200 households living within a 3 km radius of the mill. The Household Production Method was used to drive the reduced-form Dose–Response Function and the Mitigation Cost Function for assessing the impact of pollution on health and then estimating the monetary cost associated with mitigating such illnesses. The results indicate that about 60% of the respondents living in the surrounding area of the mill suffered from different respiratory illnesses. The study estimates that by reducing the suspended particulate matter (SPM) level by 50%, the expected annual welfare gains to an individual living within a 3 km radius of the mill are US $20.21. The whole community residing within a 3 km radius of the mill will enjoy an estimated welfare gain of PKR. 70.67 million (US $0.511 million). If the pollution standard limits prescribed by the World Health Organization are followed, the expected monetary benefits to all the individuals living within a 3 km radius of the mill are PKR. 114.48 million (US $0.27 million) annually.

Rainfed wheat farming directly depends upon climatic indicators and is mostly at the mercy of climatic extremes. This study analyzed the relationship between the economic efficiency of rainfed wheat farmers and indicators of climate variability in Pakistan employing a two-stage methodological framework. We used farm household level crop input-output and management data and secondary data on climate. In the first stage, a stochastic production frontier (SPF) approach was used to calculate economic efficiency. Then, in the second stage, the calculated economic efficiency scores were regressed against the temperature threshold, temperature anomaly, and total rainfall, in addition to socioeconomic, institutional, and farm variables, using OLS and quantile regression models. The results showed that temperature anomaly and the number of days when temperatures exceed 30 °C have negative and significant impacts on the economic efficiency of rainfed wheat farmers. Total rainfall showed positive and significant impacts across both OLS and quantile regression models. Further, we modeled a novel and very important variable in the context of rainfed wheat production in Pakistan, that is, farmers' participation in trainings in climate-resilient crop farming. This variable showed a positive and highly significant impact on economic efficiency of wheat farmers across all regression models. Our findings call for important policy implications, including developing up-to-date climate resilient adaptation strategies that are particularly focused on rainfed wheat farming. Establishing strong linkages between extension departments and rainfed wheat farmers could help sustain and improve the efficiency of rainfed wheat farmers and hence food and livelihood security.