Facilitated Adsorption of Mercury(II) and Chromium(VI) Ions over Functionalized Carbon Nanotubes.

By considering the importance of water and its purity, herein, a powerful adsorbent has been developed for the adsorption of two toxic contaminants that commonly exist in water, viz., divalent mercury and hexavalent chromium. The efficient adsorbent, CNTs-PLA-Pd, was prepared by covalent grafting polylactic acid to carbon nanotubes and subsequent deposition of palladium nanoparticles. The CNTs-PLA-Pd could adsorb Hg(II), and Cr(VI) entirely exists in water. The adsorption rate for Hg(II) and Cr(VI) was rapid at initial stage, followed by gradual decrease, and attained the equilibrium. The Hg(II) and Cr(VI) adsorption was perceived within 50 min and 80 min, respectively with CNTs-PLA-Pd,. Further, experimental data for Hg(II) and Cr(VI) adsorption was analyzed, and kinetic parameters were estimated using pseudo-first and second-order models. The adsorption process of Hg(II) and Cr(VI) followed the pseudo-second-order kinetics, and the rate-limiting step in the adsorption was chemisorption. The Weber-Morris intraparticle pore diffusion model revealed that the Hg(II) and Cr(VI) adsorption over CNTs-PLA-Pd occurs through multiple phases. The experimental equilibrium parameters for the Hg(II) and Cr(VI) adsorption were estimated by Langmuir, Freundlich, and Temkin isotherms models. All three models were well suited and demonstrated that Hg(II) and Cr(VI) adsorption over CNTs-PLA-Pd transpires through monolayer molecular covering and chemisorption.

Elevated Adsorption of Lead and Arsenic over Silver Nanoparticles Deposited on Poly(amidoamine) Grafted Carbon Nanotubes.

An efficient adsorbent, CNTs-PAMAM-Ag, was prepared by grafting fourth-generation aromatic poly(amidoamine) (PAMAM) to carbon nanotubes (CNTs) and successive deposition of Ag nanoparticles. The FT-IR, XRD, TEM and XPS results confirmed the successful grafting of PAMAM onto CNTs and deposition of Ag nanoparticles. The absorption efficiency of CNTs-PAMAM-Ag was evaluated by estimating the adsorption of two toxic contaminants in water, viz., Pb(II) and As(III). Using CNTs-PAMAM-Ag, about 99 and 76% of Pb(II) and As(III) adsorption, respectively, were attained within 15 min. The controlling mechanisms for Pb(II) and As(III) adsorption dynamics were revealed by applying pseudo-first and second-order kinetic models. The pseudo-second-order kinetic model followed the adsorption of Pb(II) and As(III). Therefore, the incidence of chemisorption through sharing or exchanging electrons between Pb(II) or As(III) ions and CNTs-PAMAM-Ag could be the rate-controlling step in the adsorption process. Further, the Weber-Morris intraparticle pore diffusion model was employed to find the reaction pathways and the rate-controlling step in the adsorption. It revealed that intraparticle diffusion was not a rate-controlling step in the adsorption of Pb(II) and As(III); instead, it was controlled by both intraparticle diffusion and the boundary layer effect. The adsorption equilibrium was evaluated using the Langmuir, Freundlich, and Temkin isotherm models. The kinetic data of Pb(II) and As(III) adsorption was adequately fitted to the Langmuir isotherm model compared to the Freundlich and Temkin models.

Rural Farmers' Cognition and Climate Change Adaptation Impact on Cash Crop Productivity: Evidence from a Recent Study.

The world faces a once-in-a-century transformation due to the COVID-19 pandemic, adversely affecting farmers' employment, production practices, and livelihood resilience. Meanwhile, climate change (CC) is a crucial issue limiting agricultural production worldwide. Farmers' lives, severely affected by extreme weather conditions, are resulting in the reduced production of major economic crops. The CC has drastically influenced the major agricultural sectors of Pakistan, leading to a significant decline in farmers' living standards and the overall economy. Climate-smart and eco-friendly agricultural practices can mitigate greenhouse gas emissions and ameliorate agricultural productivity under extreme environmental conditions. This paper highlights farmers' autonomous CC adaptation strategies and their influence on cash crop (maize for this study) yield under prevailing circumstances. The current study used a simultaneous equation model to examine the different adaptation impacts on adapters and non-adapters. The survey results of 498 maize farmers in rural Pakistan revealed that growers were aware of the recent CC and had taken adequate adaptive measures to acclimatize to CC. Farmers' arable land area, awareness level, and information accessibility to CC are the most crucial factors that impart a significant role in their adaptation judgments. However, most growers have inadequate adaptation strategies, including improved irrigation and the utilization of extensive fertilizers and pesticides. Using a simultaneous equation model of endogenous switching regression, the study found that farmers not adapted to CC were negatively affecting maize productivity. Therefore, this study suggests that policymakers pay attention to the countermeasures farmers have not taken to mitigate the impact of CC. In addition, policymakers should deliver appropriate adaptation strategies to assist growers in coping with climate-related natural hazards and ensure farmers' livelihood security, rural revitalization, and sustainable agricultural development.

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network.

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those 'next users' of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

What is the impact of COVID-19 pandemic on global carbon emissions?

The coronavirus 2019 (COVID 19, or SARS-CoV-2) pandemic that started in December 2019 has caused an unprecedented impact in most countries globally and continues to threaten human lives worldwide. The COVID-19 and strict lockdown measures have had adverse effects on human health and national economies. These lockdown measures have played a critical role in improving air quality, water quality, and the ozone layer and reducing greenhouse gas emissions. Using Soil Moisture Active Passive (SMAP) Level 4 carbon (SMAP LC4) satellite products, this study investigated the impacts of COVID-19 lockdown measures on annual carbon emissions globally, focusing on 47 greatly affected countries and their 105 cities by December 2020. It is shown that while the lockdown measures significantly reduced carbon emissions globally, several countries and cities observed this reduction as temporary because strict lockdown measures were not imposed for extended periods in 2020. Overall, the total carbon emissions of select 184 countries reduced by 438 Mt in 2020 than in 2019. Since the global economic activities are slowly expected to return to the non-COVID-19 state, the reduction in carbon emissions during the pandemic will not be sustainable in the long run. For sustainability, concerned authorities have to put significant efforts to change transportation, climate, and environmental policies globally that fuel carbon emissions. Overall, the presented results provide directions to the stakeholders and policymakers to develop and implement measures to control carbon emissions for a sustainable environment.

Soil CO2 emission in response to organic amendments, temperature, and rainfall.

Vegetated land surfaces play an important role in determining the fate of carbon in the global carbon cycle. However, our understanding of the terrestrial biosphere on a global scale is subject to considerable uncertainty, especially concerning the impacts of climatic variables on the carbon cycle. Soil is a source and also a sink of CO2 exchange and helps in carbon sequestration. Agricultural management practices influence soil water dynamics, as well as carbon cycling by changing soil CO2 emission and uptake rates. The rate of soil CO2 emission varies for different crops and different organic amendments. The major goal of this study was to assess the impacts of the type and rate of organic amendment on soil CO2 emission in a collard greens crop grown in the southeast Texas environment. Thirty-six plots were developed to grow collard greens on Prairie View A&M University's Research Farm. Three types of organic amendments (Chicken manure, Dairy manure, and Milorganite), at four levels of application (0, 168, 336, and 672 kg N/ha) were used and replicated three times. Each organic amendment type was applied to nine randomly selected plots. Three random plots were used as a control in each row. We measured daily soil CO2 emission for the first two weeks and every other day in a week during the experiment. We evaluated the effects of organic amendments and the application rates on soil CO2 emission for collard greens during two growing seasons. The results showed higher the application rates for each organic amendment, higher the CO2 emissions from the soil. The results also showed higher cumulative CO2 emissions for the soils amended with chicken manure and milorganite, but lowest for the soils amended with dairy manure. This field experiment and analyses help better understand the temporal and spatial variations of soil CO2 emission, and also help to develop best management practices to maximize carbon sequestration and to minimize soil CO2 emissions during the growth periods of collard greens under changing temperatures using different organic amendments, and application rates.

Estimating land surface variables and sensitivity analysis for CLM and VIC simulations using remote sensing products.

Assessment of Land Surface Models (LSMs) at heterogeneous terrain and climate regimes is essential for understanding complex hydrological and biophysical parameterization. This study utilized the two LSMs, Community Land Model (CLM 4.0) and three layer Variable Infiltration Capacity (VIC-3L), to estimate the interaction between land surface and atmosphere by means of energy fluxes including net radiation (RN), sensible heat flux (H), latent heat flux (LE), and ground heat flux (G). The modeled energy fluxes were analyzed at two sites: Freeman Ranch-2 (FR2) located in the lowland region of Texas (272m), and Providence 301 (P301) located on the mountains of Sierra Nevada in California (2015m) from 2003 to 2013. RN was underestimated by CLM with bias -25.06Wm-2 due to its snow hydrology scheme at P301. LE was overestimated by the VIC during summer precipitation and had a positive bias of 5.51Wm-2, whereas CLM showed a negative bias of -6.58Wm-2 at the FR2 site. G was considered as a residual term in CLM, which caused weak performance at P301, while VIC calculated G as a function of soil temperature, depth, and hydraulic conductivity. In addition, The MOD16 showed similar results with models at FR2; however, at P301, they yielded a correlation value of 0.85 and 0.21 for LSMs and MOD16, respectively. The later has lower correlation with in situ specifically in summer season caused by erroneous biophysical or meteorological inputs to the algorithms. The sensitivity analysis between soil moisture and turbulent fluxes, exhibited negative trend (especially for LE at P301) due to topography and snow cover. The results from this study are conducive to improvements in models and satellite based characterization of water and energy fluxes, especially at rugged terrain with high elevation, where observational experiments are difficult to conduct.