Hierarchical NiCo@NiOOH@CoMoO4 Core-Shell Heterostructure on Carbon Cloth for High-Performance Asymmetric Supercapacitors.

The fabrication of low-cost, effective, and highly integrated nanostructured materials through simple and reproducible methods for high-energy-density supercapacitors is highly desirable. Herein, an activated carbon cloth (ACC) is designed as the functional scaffold for supercapacitors and treated hydrothermally to deposit NiCo nanoneedles working as internal core, followed by a dip-dry coating of NiOOH nanoflakes core-shell and uniform hydrothermal deposition of CoMoO4 nanosheets serving as an external shell. The structured core-shell heterostructure ACC@NiCo@NiOOH@CoMoO4 electrode resulted in exceptional specific areal capacitance of 2920 mF cm-2 and exceptional cycling stability for 10 000 cycles. Moreover, the fabricated electrode is developed into an asymmetric supercapacitor which demonstrates excellent areal capacitance, energy density, and power density within the broad potential window of 1.7 V with a cycling life of 92.4% after 10 000 charge-discharge cycles, which reflects excellent cycle life. The distinctive core-shell structure, highly conductive substrate, and synergetic effect of coated material results in more electrochemical active sites and flanges for effective electrons and ion transportation. This unique technique provides a new perspective for cost-efficient supercapacitor applications.

Estimating CO2 emissions from emergency-supply transport: The case of COVID-19 vaccine global air transport.

The environmental cost of disaster-related emergency supplies is significant. However, little research has been conducted on the estimation of emergency-supply transportation-related carbon emissions. This study created an "emergency supply emission estimation methodology" (ESEEM). The CO2 emissions from the global air dispatch of COVID-19 vaccines were estimated using two hypothetical scenarios of one dose per capita and additional doses secured. The robustness of the model was tested with the Monte Carlo Simulation method (MCM) based one-sample t-test. The model was validated using the "Expression of Uncertainty in Measurement (GUM)" and GUM's MCM approaches. The results showed that to dispatch at least one dose of the COVID-19 vaccine to 7.8 billion people, nearly 8000 Boeing 747 flights will be needed, releasing approximately 8.1 ± 0.30 metric kilotons (kt) of CO2. As countries secure additional doses, these figures will increase to 14,912 flights and about 15 ± 0.48 kt of CO2. According to the variance-based sensitivity analysis, the total number of doses (population), technology, and wealth play a significant role in determining CO2 emissions across nations. Thus, wealthy nations' long-term population reduction efforts, technological advancements, and mitigation efforts can benefit the environment as a whole and the CO2 burdens associated with current COVID-19 and any future disasters' emergency-supply transportation.

Environmental impacts of shifts in energy, emissions, and urban heat island during the COVID-19 lockdown across Pakistan.

Restrictions on human and industrial activities due to the coronavirus (COVID-19) pandemic have resulted in an unprecedented reduction in energy consumption and air pollution around the world. Quantifying these changes in environmental conditions due to government-enforced containment measures provides a unique opportunity to understand the patterns, origins and impacts of air pollutants. During the lockdown in Pakistan, a significant reduction in energy demands and a decline of ∼1786 GWh (gigawatt hours) in electricity generation is reported. We used satellite observational data for nitrogen dioxide (NO2), carbon monoxide (CO), sulphur dioxide (SO2), aerosol optical depth (AOD) and land surface temperature (LST) to explore the associated environmental impacts of shifts in energy demands and emissions across Pakistan. During the strict lockdown period (March 23 to April 15, 2020), we observed a reduction in NO2 emissions by 40% from coal-based power plants followed by 30% in major urban areas compared to the same period in 2019. Also, around 25% decrease in AOD (at 550 nm) thickness in industrial and energy sectors was observed although no major decrease was evident in urban areas. Most of the industrial regions resumed emissions during the 3rd quarter of April 2020 while the urban regions maintained reduced emissions for a longer period. Nonetheless, a gradual increase has been observed since April 16 due to relaxations in lockdown implementations. Restrictions on transportation in the cities resulted in an evident drop in the surface urban heat island (SUHI) effect, particularly in megacities. The changes reported as well as the analytical framework provides a baseline benchmark to assess the sectoral pollution contributions to air quality, especially in the scarcity of ground-based monitoring systems across the country.

Belt and road initiative as a catalyst of infrastructure development: Assessment of resident's perception and attitude towards China-Pakistan Economic Corridor.

The Chinese Government commenced the One Belt One Road (OBOR) project in 2013 for the multidimensional development to restore the historical Silk Road paradigms. The Economic Corridor provides networks and connections based on two geographical territories. The China Pakistan Economic Corridor (CPEC) is one of them, a chunk of the Silk Road Economic Belt's economic corridors. CPEC would be an economic game-changer for Pakistan. It will generate businesses, minimize poverty, generate employment opportunities, and improve local communities' health and education. However, it is more lucrative for the Chinese economy because CPEC is a safe, cheapest, and shortest route for importing energy rather than other routes. The present study investigates the social, infrastructural, and tourism effects of CPEC through the mediation role of rural development and knowledge sharing, including income, employment, business, land-use change variables, and CPEC adoptability for a local community in Pakistan. This study is based on four different regions of Gilgit Baltistan, Khyber Pakhtunkhwa, Punjab, and Sindh in Pakistan. The study incorporates the collected data from the respondents living on the CPEC routes via face-to-face interviews from citizens (cities, villages, and towns). Besides, the study applied univariate and Structural Equation Model techniques to draw the results. The study results reveal that CPEC plays a significant role in Pakistan's socio-economic and rural development. This mega project's expectations might bring positive changes in infrastructure development, energy sector, and social development projects in Pakistan. The Results also indicated that CPEC would link rural areas to urban areas, which would offer development opportunities for rural regions to achieve sustainable development.

Associations of air pollution concentrations and energy production dynamics in Pakistan during lockdown.

This study investigated atmospheric changes that occurred due to changes in energy production and consumption before and during the COVID-19 pandemic. We analyzed nitrogen dioxide (NO2), aerosol optical depth (AOD), and rainfall patterns to understand the associated changes in emissions, especially from the power generation sector, before (2018 and 2019) and during the lockdown of 2020 across Pakistan. Regression analysis indicated a strong association between energy production by thermal power plants and tropospheric NO2 concentrations. Notably, a comparison between emission sources showed that the NO2 emissions from a single thermal power plant were equivalent to the emissions from a major city. During the lockdown, we observed a 40% reduction in NO2 emissions from coal-based power plants and a 30% reduction in mega- and major cities compared to the same retro in 2019. We also observed an approximate 25% decrease in AOD in the industrial and energy sectors, although no major decrease was obvious in the cities. Rainfall contributed to reducing the NO2 concentrations during monsoon season across all power plants in Pakistan, whereas it did not significantly correlate with AOD. The findings highlight the need for appropriate management and use of renewable energy in the industrial sector and transportation systems. Future research could estimate the environmental and public health costs linked to pollution originating from thermal energy production and poor transportation infrastructure.

Environmental spatial heterogeneity of the impacts of COVID-19 on the top-20 metropolitan cities of Asia-Pacific.

This study investigated the environmental spatial heterogeneity of novel coronavirus (COVID-19) and spatial and temporal changes among the top-20 metropolitan cities of the Asia-Pacific. Remote sensing-based assessment is performed to analyze before and during the lockdown amid COVID-19 lockdown in the cities. Air pollution and mobility data of each city (Bangkok, Beijing, Busan, Dhaka, Delhi, Ho Chi Minh, Hong Kong, Karachi, Mumbai, Seoul, Shanghai, Singapore, Tokyo, Wuhan, and few others) have been collected and analyzed for 2019 and 2020. Results indicated that almost every city was impacted positively regarding environmental emissions and visible reduction were found in Aerosol Optical Depth (AOD), sulfur dioxide (SO2), carbon monoxide (CO), and nitrogen dioxide (NO2) concentrations before and during lockdown periods of 2020 as compared to those of 2019. The highest NO2 emission reduction (~ 50%) was recorded in Wuhan city during the lockdown of 2020. AOD was highest in Beijing and lowest in Colombo (< 10%). Overall, 90% movement was reduced till mid-April, 2020. A 98% reduction in mobility was recorded in Delhi, Seoul, and Wuhan. This analysis suggests that smart mobility and partial shutdown policies could be developed to reduce environmental pollutions in the region. Wuhan city is one of the benchmarks and can be replicated for the rest of the Asian cities wherever applicable.

Drinking-water efficiency, cost of illness, and peri-urban society: An economic household analysis.

This study aims to measure the efficacy of drinking water in terms of the economic impacts and risk of illness involved in using perilous water sources. Socio-economic factors were also considered. A multidisciplinary approach was employed to analyze the data, including the cost of illness (COI), regression technique, and irrigation water efficiency methods. The primary data set consisted of 210 peri-urban and urban households. It was found that the average cost of illness was higher in peri-urban ($10.79 USD) areas, while willingness to pay for quality water was higher in urban residents. Social status, income, and family size was positively associated with the cost of illness, while education, the source of drinking water (ground water and others), and awareness about safe drinking were negatively associated with the cost of illness. Furthermore, urban residents were more efficient in terms of conveyance and water use. This is one of the first studies to apply irrigation water efficiency methods to measure drinking water efficiency. The results are timely and important with both practical and social implications, including guiding policy framework. It is suggested that family planning programs be made more effective to control family size. The filtration plants to enhance drinking water quality be installed in the central places of each town/division/union council. A public-private partnership could work to provide affordable quality drinking water.

Spatial-temporal characterization of rainfall in Pakistan during the past half-century (1961-2020).

Spatial-temporal rainfall assessments are integral to climate/hydrological modeling, agricultural studies, and water resource planning and management. Herein, we evaluate spatial-temporal rainfall trends and patterns in Pakistan for 1961-2020 using nationwide data from 82 rainfall stations. To assess optimal spatial distribution and rainfall characterization, twenty-seven interpolation techniques from geo-statistical and deterministic categories were systematically compared, revealing that the empirical Bayesian kriging regression prediction (EBKRP) technique was best. Hence, EBKRP was used to produce and utilize the first normal annual rainfall map of Pakistan for evaluating spatial rainfall patterns. While the largest under-prediction was estimated for Hunza (- 51%), the highest and lowest rainfalls were estimated for Malam Jaba in Khyber Pakhtunkhwa province (~ 1700 mm), and Nok-kundi in Balochistan province (~ 50 mm), respectively. A gradual south-to-north increase in rainfall was spatially evident with an areal average of 455 mm, while long-term temporal rainfall evaluation showed a statistically significant (p = 0.05) downward trend for Sindh province. Additionally, downward inter-decadal regime shifts were detected for the Punjab and Sindh provinces (90% confidence). These results are expected to help inform environmental planning in Pakistan; moreover, the rainfall data produced using the optimal method has further implications in several aforementioned fields.

Infrastructure projects and sustainable development: Discovering the stakeholders' perception in the case of the China-Pakistan Economic Corridor.

The China-Pakistan Economic Corridor (CPEC) has been an economic game changer for both China and Pakistan. We investigate stakeholder satisfaction with CPEC projects in Pakistan, particularly with respect to the affected local communities. Given the project application and adaptability, two provinces-Khyber Pakhtunkhwa and Punjab-and eight districts were selected randomly. Primary data from approximately 250 respondents as well as secondary data were collected. Among other models, a logit model was adopted to determine the role of certain factors in the perceived level of satisfaction. Results reveal that with respect to the relationship between land acquisition and dissatisfaction with a CPEC project, the level of dissatisfaction is 2.45 times higher when land is acquired by force or when compensation for the land is perceived to be inadequate by the local people. Individuals favor economic zones and development projects over road projects; the likelihood of being dissatisfied is approximately nine times greater in regions without economic zones than that in regions with such zones. Similarly, when no development project is allocated to a community, the probability of dissatisfaction of the local people is about 7.6 times greater. In addition, expectations of poor financial outcomes for CPEC projects cause significant dissatisfaction and are a source of tension among the local people. To reduce dissatisfaction, organizations and business communities must actively support the success of CPEC projects. A more equitable allocation of economic zones and development projects may help ease tensions and increase satisfaction among the local people.

Pricing behavior of monopoly market with the implementation of green technology decision under emission reduction subsidy policy.

Carbon emissions are one of the major constraints considered under a Cap-and-Trade (C-and-T) system, regarding the implementation of green technologies in the operations of emissions-generating companies. Green technology implementation, based on optimal pricing decisions, has become an inevitability due to rising carbon emissions. We studied the profit-maximizing behavior of a firm considering whether to implement of green technology due to subsidies offered on emission-reduction rates. In order to achieve the desired results, we used a simulation-based model and developed a conceptual model for the verification of functions. When the product price was high, the firm achieved a high profit, which was the main focus of the firm. The firm thus had sufficient resources to implement green technology. However, when the product price was low, the firm could achieve its goal of profit maximization, but did so without implementing green technology. To solve this problem, we studied government involvement in the market to incentivize emissions reduction and to benefit the firm. We decided to model emissions-reduction policy to encourage the implementation of green technology and support firm profits. We found that subsidies enabled a firm to maximize its profits while ensuring green technology implementation, while the firm would not have adopted green technology without subsidies or mandates. This study should help decision makers understand pricing strategies in the maximization of the profit. Additionally, this study helps demonstrate that the government plays an important role in monopolized markets by reducing negative externalities.

Climate change and associated spatial heterogeneity of Pakistan: Empirical evidence using multidisciplinary approach.

Climate change is a multidimensional phenomenon, which has various implications for the environment and socio-economic conditions of the people. Its effects are deeper in an agrarian economy which is susceptible to the vagaries of nature. Therefore, climate change directly impacts the society in different ways, and society must pay the cost. Focusing on this truth, the main objective of this research was to investigate the empirical changes and spatial heterogeneity in the climate of Pakistan in real terms using time series data. Climate change and variability in Pakistan, over time, were estimated from 1961 to 2014 using all the climate variables for the very first time. Several studies were available on climate change impacts, mitigation, and adaptation; however, it was difficult to observe exactly how much change occurred in which province and when. A multidisciplinary approach was utilized to estimate the absolute change through a combination of environmental, econometric, and remote sensing methods. Moreover, the Autoregressive Distributed Lag (ARDL) model was used to ascertain the extent of variability in climate change and information was digitalized through ground truthing. Results showed that the average temperature of Pakistan increased by 2°C between 1960 and 1987 and 4°C between 1988 and 2014, and R2 was 0.978. The rate of temperature increased 0.09°C between 1960 and 2014. The mean annual precipitation of Pakistan increased by 478mm, and its R2 were 0.34-0.64. The mean annual humidity of Pakistan increased by 2.94%, and the rate of humidity has been increased by 0.97% from 1988 to 2014. Notably, Sindh and Balochistan provinces have shown a significant spatial heterogeneity regarding the increase in precipitation. Statistically all variables are significant. This would serve as a baseline information for climate change-related studies in Pakistan and its application in different sectors. This would also serve the plant breeders and policymakers of the country.

Climate mitigation, low-carbon society, and dynamism of educational institutes in a low-income country.

This paper aims to investigate carbon footprints of faculty members of University of Agriculture Faisalabad (UAF) associated with income and education in pursuance of a low-carbon society. For the study, 140 UAF faculty members (professors, associate professors, assistant professors, and lecturers) were selected using stratified random sampling technique, and a representative questionnaire was used to record primary data. Moreover, the ordinary least square (OLS) method was used to explain the statistical relationship between income, education, and carbon footprints. It was found that carbon footprints of UAF faculty members were 10.06 metric tons (mt) per year per person on an average. Our results further indicated that carbon footprints of assistant professors, associate professors, and professors were 10.83, 11.95, and 10.96 mt per person per annum, respectively. OLS estimates showed that an increase in one Doctor of Philosophy (Ph.D.) faculty member increases the carbon footprint by 1.15 mt per annum. Male faculty members emit more carbon footprints than females. Faculty members of Tenure Track System (TTS) had a higher income than those of Basic Pay Scale (BPS). Therefore, emissions of TTS faculty members were higher. Hence, in order to reduce carbon footprints and corroborate UAF campus environment-friendly, the attitude towards this aspect should be changed and awareness should be created. Furthermore, reduced car usage can be another bottom-up policy suggestion. As witnessed in green campuses of international universities, UAF should also be a motor-free campus (cycling and pedestrian only).

Migration, health, and socioenvironmental safety net among children of Dhaka, Bangladesh.

This study quantifies the diarrhea burden among migrant children under age 5 (who have migrated due to environmental degradation) in Dhaka. We used a multifactor socioepidemiological as well as environmental approach with pretested questionnaires and observations. It was found that 52% of the children were affected by diarrhea. Disability-adjusted life years (DALYs) lost was reduced manifold with the increase of mothers' behavioral determinants. Health losses were 1,718 fold with significant coefficient (ß) in the migrant group. DALYs lost were significantly associated with socioenvironmental factors such as mother's illiteracy (ß = .18; p < .001), no hand wash before eating (ß = .08; p = .004), and no hand wash after defecation (ß = .10; p < .001). This puts emphasis clearly on the awareness at household level, especially of mothers and children under age 5 in Dhaka, Bangladesh, in formulating migration-related policies.