ORCID Profile
0000-0002-6079-715X
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Publisher: MDPI AG
Date: 12-2022
DOI: 10.3390/SU142316035
Abstract: Remarkable agricultural productivity gains have been achieved during the last several decades as a result of green revolution (GR) technologies that have greatly increased food production and reduced hunger. However, climate change threatens to reverse the progress made so far in the fight against food insecurity. The agricultural sector in many developing countries, including the rice and wheat producers such as in Punjab (Pakistan and India), is highly vulnerable to climate change, which has serious implications for rural livelihoods and food security. Adaptation is considered a key tool to tackle climate challenges at the farm level and is, therefore, the focus of this study in terms of its impact on rice yields. A household survey was conducted in the Punjab province of Pakistan, and farmers were interviewed face-to-face. We employed a simultaneous equations model to assess the differential impacts of climate change adaptation on adapting and non-adapting farmers’ rice yields. Using the cross-sectional data of 480 rice growers, an endogenous switching regression model provided a means to estimate the selection bias of farmers’ attributes. The results show a significant positive impact of adaptations on rice yields. Specifically, the yield of farmers who adapted to climate change was 24% higher than the non-adapting farmers. The results further indicate that non-adapters can also benefit from the adaptation strategies if they decide to adapt. We also found a significant positive effect of farmers’ climate risk perceptions, literacy level, access to irrigation, ownership of livestock, and availability of farm advisory services on their adaptation decisions. These results, therefore, suggest that policymakers should take into account farmers’ local adaptation knowledge and farming practices when formulating adaptation policies.
Publisher: MDPI AG
Date: 08-07-2022
DOI: 10.3390/SU14148401
Abstract: As growth regions evolve to accommodate the increasing population, they need to develop a wider variety of residential properties to accommodate the varying needs of the residents. As a result, the new accommodation is denser which involves higher embodied water carbon and energy. This research compares the construction differences in metropolitan and growth regions of Melbourne to identify embodied carbon, water, and energy. Representative areas of 25 km2 are selected from both regions. The growth region has 80% of the built area comprised of 2nd generation low-rise residential buildings whereas the prolific construction type in the Metropolitan region is mixed purpose industrial with 30% of the built area comprising of this type. The methodology implies open-source satellite imagery to build a spatial dataset in QGIS. The visual identification of the constructions in the study areas enables to identity the materials used in their construction. The total embodied carbon, water, and energy for the Metropolitan region are 32,895 tonnes, 4192 mL, and 3,694,412 GJ, respectively, whereas in the growth region, the totals are 179,376 tonnes carbon, 2533 mL water, and 2,243,571 GJ. Whilst Metropolitan has a significantly higher overall footprint when this is compared to the population of each region, it is shown that the growth region with its current construction type has a higher embodied carbon, water, and energy per head. The total per head for Metropolitan is 226.7 GJ energy, 257 kL water, and 20 tonnes carbon, whereas in the growth region, the embodied energy, water, and carbon, respectively, per head is 287.4 GJ, 324.6 kL, and 22 tonnes. The current performance per head of the growth region is considerably lower than that of Metropolitan. Using erse residential construction types and efficient materials can serve the demanding needs of denser populated areas.
Publisher: MDPI AG
Date: 17-08-2022
DOI: 10.3390/SU141610196
Abstract: In Pakistan, research on information and communication technologies-based agricultural information services (ICTbAIS) have gained significant attention owing to the overwhelming population of smallholder farmers (whose information needs are unable to be met by the conventional extension services) and the increasing incidence of climatic risk. This study is, therefore, conducted in the Punjab province of Pakistan (mixed cropping region) to explore farmers’ use of ICTbAIS and understand the relationship between farmers’ socio-economic attributes, risk perception, and choices of ICTbAIS. A s le of 480 farmers was drawn using a multistage s ling approach, and farmers were interviewed face-to-face. To analyze the dataset, a multivariate Probit (MVP) model was employed. The results show that Television (TV) and mobile-based advisory and mobile-based consultations appeared to be the most used ICTbAIS, followed by radio and internet-based advisory. The estimates of the MVP model showed that farmers’ age, education, farmland, tenancy status, off-farm income, and climate risk perception are significant determinants of their choices of ICTbAIS. Based on our results, we suggest policymakers and extension agencies to improve the content of ICTbAIS and make efforts for the awareness and training of farmers regarding the use of contemporary ICTs.
Publisher: MDPI AG
Date: 21-03-2022
DOI: 10.3390/W14060992
Abstract: Managing and communicating flood risks necessitates a strong understanding of how people perceive risk. It has become critical to examine risk perception to implement effective disaster risk management (DRM) measures. Socioeconomic determinants have an impact on risk perception, which in turn affects future adaptive capacity and disaster preparedness. First and foremost, this research attempts to determine how Pakistani people in rural areas perceive flood risk, and second, to examine the factors that can influence rural residents’ perceptions of flood risk. The data for this study were collected through face-to-face interviews with 600 respondents (household heads) from Charsadda and Nowshera districts that were severely affected by the 2010 flood. A flood risk perception index was developed (using a risk matrix) using relevant attributes on a Likert scale and classified into two categories: high and low perceived risk. Furthermore, a binary regression model was used to examine the influence of socioeconomic and institutional factors on rural households’ risk perception. Flood risk was perceived by 67 percent of the total s led participants in the study regions. The results of binary logistic regression demonstrate that flood risk perception is strongly linked to socioeconomic variables such as age, education, house ownership, family size, past flood experience, and distance from the nearest river source, as well as institutional factors such as access to credit and extreme weather forecast information. The findings of the current study additionally revealed that flood risk perception varied among household heads based on education (1–10 years perceived high flood risk (51.47%)), age (age greater than 40 years perceived high flood risk (52.83%)), and monthly income levels (lower monthly income group perceived high flood risk (73.02%)). The findings of this study shed light on rural households’ perception of flood risk and the factors that shape such perceptions. These findings can assist provincial and local disaster management authorities in better understanding flood risk and adopting local actions that could be used to respond to flood and other climate-related disasters.
No related grants have been discovered for Nasir Abbas Khan.