Integrating work into life helps reduce residential greenhouse gas emissions.

Work from home (WFH) creates work-life integration by moving work into traditional life at home, but its influence on residential greenhouse gas (GHG) emissions remains unclear. In this study, an activity-based bottom-up model was developed to analyze the time-use patterns (activity durations and timeline of a typical day) of participants under WFH and traditional home life and to quantify their residential GHG emissions. Under WFH, participants generated an average of 9.03 kg CO2e/person/day, primarily attributed to space heating and cooling, cooking, grooming, work, and watching TV and movies. Notably, the GHG footprints varied across groups (8.08-9.93 kg CO2e/person/day) due to different work and household responsibilities and leisure time and varied with climate region (4.99-10.63 kg CO2e/person/day) because of emission factors of electricity, space heating and cooling, and cooking. Compared with traditional life at home (10.06 kg CO2e/person/day), WFH participants spent less time on almost all major activities (especially sleeping and watching TV and movies) to focus on work, enabling an 11.34% (1.02 kg CO2e/person/day) mitigation of GHG emissions. The reductions also varied by group and climate region, mainly associated with laundry, cooking, and watching TV and movies. Opportunities to reduce GHG emissions under WFH lie in targeting key activities, balancing the time spent on various activities, and developing group- and spatial-specific strategies. This study provides a systematic and high-resolution estimation of residential GHG emissions under WFH and traditional home life, with a complete system boundary, activity-specific considerations, and countrywide understanding. The findings reveal the environmental impact of work-life integration from the residential perspective and can aid residents and policymakers in utilizing decarbonization opportunities to advance low-carbon living under WFH.

Comparative lifecycle greenhouse gas emissions and their reduction potential for typical petrochemical enterprises in China.

Petrochemical enterprises have become a major source of global greenhouse gas (GHG) emissions. Yet, due to the unavailability of basic data, there is still a lack of case studies to quantify GHG emissions and provide petrochemical enterprises with guidelines for implementing energy conservation and emission reduction strategies. Therefore, this study conducted a life cycle assessment (LCA) analysis to estimate the GHG emissions of four typical petrochemical enterprises in China, using first-hand data, to determine possible emission reduction measures. The analytical data revealed that Dushanzi Petrochemical (DSP) has the highest GHG emission intensity (1.17 tons CO2e/ton), followed by Urumqi Petrochemical (UP) (1.08 tons CO2e/ton), Dalian Petrochemical (DLP) (average 0.58 tons CO2e/ton) and Karamay Petrochemical (KP) (average 0.50 tons CO2e/ton) over the whole life cycle. At the same time, GHG emissions during fossil fuel combustion were the largest contributor to the whole life cycle, accounting for about 77.31%-94.27% of the total emissions. In the fossil-fuel combustion phase, DSP had the highest unit GHG emissions (1.20 tons CO2e), followed by UP (0.89 tons CO2e). In the industrial production phase, DLP had the highest unit GHG emissions (average 0.13 tons CO2e/ton), followed by UP (0.10 tons CO2e/ton). During the torch burning phase, torch burning under accident conditions was the main source of GHG emissions. It is worth noting that the CO2 recovery stage has "negative value," indicating that it will bring some environmental benefits. Further scenario analysis shows that effective policies and advanced technologies can further reduce GHG emissions.

Widening the applicability of AnMBR for urban wastewater treatment through PDMS membranes for dissolved methane capture: Effect of temperature and hydrodynamics.

AnMBR technology is a promising alternative to achieve future energy-efficiency and environmental-friendly urban wastewater (UWW) treatment. However, the large amount of dissolved methane lost in the effluent represents a potential high environmental impact that hinder the feasibility of this technology for full-scale applications. The use of degassing membranes (DM) to capture the dissolved methane from AnMBR effluents can be considered as an interesting alternative to solve this problem although further research is required to assess the suitability of this emerging technology. The aim of this study was to assess the effect of operating temperature and hydrodynamics on the capture of dissolved methane from AnMBR effluents by DMs. To this aim, a commercial polydimethylsiloxane (PDMS) DM was coupled to an industrial prototype AnMBR (demonstration scale) treating UWW at ambient temperature. Different operating temperatures have been evaluated: 11, 18, 24 and 30 °C. Moreover, the DM was operated at different ratios of liquid flow rate to membrane area (QL:A) ranging from 22 to 190 Lh-1m-2 in order to study the resistance of the system to methane permeation. Methane recovery was maximized when temperature raised and QL:A was reduced, giving methane recovery efficiencies (MRE) of about 85% at a temperature of 30 °C and a QL:A of 25 Lh-1m-2. The study showed that high QL:A ratios hinder methane recovery by the perturbation of the DM fibers, being this effect intensified at lower temperatures probably due the higher liquid viscosities. Also, the performed fouling evaluation showed that not significant membrane fouling may be expected in the DM unit at the short-term when treating AnMBR effluents. A resistance-in-series model was proposed to predict the overall mass transfer of the system according to operating temperature and QL:A, showing that methane capture was controlled by the liquid phase, which represented up to 80-90% of total mass transfer resistance. The energy and environmental evaluation performed in this study revealed that PDMS DMs would enhance energy recovery and environmental feasibility of AnMBR technology for UWW treatment, especially when operating at low temperatures. When MRE was maximized, the combination of AnMBR with DM achieved net energy productions and net greenhouse gas reductions of up to 0.87 kWh and 0.216 kg CO2-eq per m3 of treated water.

How does the global plastic waste trade contribute to environmental benefits: Implication for reductions of greenhouse gas emissions?

Plastic waste pollution has been identified as a serious global issue, posing environmental risks in terms of massive waste generation, ocean pollution, and increases in greenhouse gas (GHG) emissions. Despite documented environmental impacts, it remains debatable whether the global plastic waste trade (GPWT) for reutilization and recycling, as part of the global circular economy (CE), has historically contributed to environmental benefits. To investigate if historical GPWT has contributed to environmental benefits in terms of reductions of GHG emissions, this study analyzed GPWT between China and trading countries through their trajectories, characteristics and driving forces of reductions of GHG emissions between 1992 and 2017. Results indicated an increasing trend of reductions of GHG emissions in GPWT between China and trading countries over 25 years. A net reduction of 8.27 million metric tons carbon dioxide equivalent (CO2e) was observed in 2012, nearly 84 times levels observed in 1992. Policy implications after China's recent ban of imports of GPWT in December 2017 and recent changes of GPWT to other Asian countries are discussed. Dramatic changes in sustainable approaches to GPWT for reutilization and recycling are required.

Investigation of the urbanization contribution to the COVID-19 outbreak in Iran and the MECA countries.

The main objective of this research was to disclose the correlative contribution of urban-associated factors affecting the COVID-19 outbreak in the macro-scale of MECA countries and the downscaled micro-scale of the provincial divisions in Iran. For this purpose, the correlation coefficients between the variables and clustering analysis were used to expose the possible effects. Results revealed the comparatively strong relationships between some independent variables (e.g., total greenhouse gas emissions, CO2 emissions, nitrous oxide emissions, and urban population) and confirmed cases (R from 0.619 to 0.695), demonstrating the possible effective role of urbanization and its induced GHG emissions on the COVID-19 outbreak in the country level of the MECA region. Therefore, the results significantly confirmed the strong relationships between some independent variables (e.g., total population, urban population, fuel consumption, NO2-CO2 emissions, energy use, and total intra-changed travels) and confirmed cases (R from 0.724 to 0.945), explaining an explicit relationship between urbanization processes and the COVID-19 outbreak in Iran. Besides, the HCA results revealed the substantial role of the urban population and urban-induced energy use and gas emission in clustering locations regarding the COVID-19 outbreak in both the MECA region and Iran. The main implication of this research is to give a practical correlation between Coronavirus infection and urban constitution, aiming to increase the health of urban societies by creating effective planning in the future.

Trends of carbon emissions from applications of nitrogen fertiliser and crop residues to agricultural soils in South Africa.

The Agriculture, Forestry and Other Land Use (AFOLU) sector produces approximately 10% of the global anthropogenic greenhouse gas (GHG) emissions and growing demands for food to meet the needs of an increasing population make it difficult to mitigate these emissions. This study investigated historical (1911-2018) nitrous oxide (N2O) emissions from applications of synthetic nitrogen (N) fertiliser for agricultural purposes and crop residues retained in the fields post-harvest in South Africa. The aim was to develop trends of different sources of these emissions to guide national mitigation plans. Disaggregation of the emissions from key crops were developed using area planted, N application rates and residues retained in the fields. N2O intensities were calculated to establish a relationship between agricultural emissions and socio-economic conditions. Total emissions from N and crop residues were 7.3 million tonnes (Mt) of carbon dioxide equivalent (CO2e) emissions in 2018 and N2O from N fertiliser was approximately 3.0 Mt. Arrival of subsidised synthetic N in the 1950s grew the emissions significantly until they peaked in the 1980s when the support was terminated. N2O emissions per capita are gradually decreasing with time which indicates an unsustainable situation of population growing faster than its ability to produce food for itself. Less emissions per kilocalorie further indicate that crop emissions are not carbon intensive.

Pollution, management, and mitigation of idle and orphaned oil and gas wells in Alberta, Canada.

Alberta has extensive non-renewable energy resources which contribute to the Canadian economy. A downturn in oil and gas energy prices in 2014 contributed to increased idle and orphaned wells, posing potential environmental and human health risks, as well as an economic burden on the province of Alberta. Idle and orphaned wells contribute to local adverse environmental and human health effects from soil and groundwater contamination to greenhouse gas emissions. With increasing numbers of idle and orphaned wells, current monitoring measures, including regulation and cost to identify well leakage, are insufficient. Current policy measures to manage idle and orphaned well environmental liabilities were found to be inadequate to cover cleanup costs. With oil and gas prices showing no signs of rebound, these idle and orphaned well liabilities need to be addressed. This paper discusses potential environmental risks that idle and orphaned oil and gas wells pose, compares Alberta's current monitoring and policy initiatives to those in other provinces as well as the USA, and recommends future management strategies to mitigate the issue.

Electricity carbon intensity in European Member States: Impacts on GHG emissions of electric vehicles.

The Well-To-Wheels (WTW) methodology is widely used for policy making in the transportation sector. In this paper updated WTW calculations are provided, relying on 2013 statistic data, for the carbon intensity (CI) of the European electricity mix; detail is provided for electricity consumed in each EU Member State (MS). An interesting aspect presented is the calculation of the GHG content of electricity traded between Countries, affecting the carbon intensity of the electricity consumed at national level. The amount and CI of imported electricity is a key aspect: a Country importing electricity from another Country with a lower CI of electricity will lower, after the trade, its electricity CI, while importing electricity from a Country with a higher CI will raise the CI of the importing Country. In average, the CI of electricity used in EU at low voltage in 2013 was 447 gCO2eq/kWh, which is the 17% less compared to 2009. Then, some examples of calculation of GHG emissions from the use of electric vehicles (EVs) compared to internal combustion engine vehicles are provided. The use of EVs instead of gasoline vehicles can save (about 60% of) GHG in all or in most of the EU MSs, depending on the estimated consumption of EVs. Compared with diesel, EVs show average GHG savings of around 50% and not savings at all in some EU MS.

"Hot spots" of N and C impact nitric oxide, nitrous oxide and nitrogen gas emissions from a UK grassland soil.

Agricultural soils are a major source of nitric- (NO) and nitrous oxide (N2O), which are produced and consumed by biotic and abiotic soil processes. The dominant sources of NO and N2O are microbial nitrification and denitrification, and emissions of NO and N2O generally increase after fertiliser application. The present study investigated the impact of N-source distribution on emissions of NO and N2O from soil and the significance of denitrification, rather than nitrification, as a source of NO emissions. To eliminate spatial variability and changing environmental factors which impact processes and results, the experiment was conducted under highly controlled conditions. A laboratory incubation system (DENIS) was used, allowing simultaneous measurement of three N-gases (NO, N2O, N2) emitted from a repacked soil core, which was combined with 15N-enrichment isotopic techniques to determine the source of N emissions. It was found that the areal distribution of N and C significantly affected the quantity and timing of gaseous emissions and 15N-analysis showed that N2O emissions resulted almost exclusively from the added amendments. Localised higher concentrations, so-called hot spots, resulted in a delay in N2O and N2 emissions causing a longer residence time of the applied N-source in the soil, therefore minimising NO emissions while at the same time being potentially advantageous for plant-uptake of nutrients. If such effects are also observed for a wider range of soils and conditions, then this will have major implications for fertiliser application protocols to minimise gaseous N emissions while maintaining fertilisation efficiency.

Rolling resistance contribution to a road pavement life cycle carbon footprint analysis.

PURPOSE: Although the impact of road pavement surface condition on rolling resistance has been included in the life cycle assessment (LCA) framework of several studies in the last years, there is still a high level of uncertainty concerning the methodological assumptions and the parameters that can affect the results. In order to adopt pavement carbon footprint/LCA as a decision-making tool, it is necessary to explore the impact of the chosen methods and assumptions on the LCA results. METHODS: This paper provides a review of the main models describing the impact of the pavement surface properties on vehicle fuel consumption and analyses the influence of the methodological assumptions related to the rolling resistance on the LCA results. It compares the CO2 emissions, calculated with two different rolling resistance models existing in literature, and performs a sensitivity test on some specific input variables (pavement deterioration rate, traffic growth, and emission factors/fuel efficiency improvement). RESULTS AND DISCUSSION: The model used to calculate the impact of the pavement surface condition on fuel consumption significantly affects the LCA results. The pavement deterioration rate influences the calculation in both models, while traffic growth and fuel efficiency improvement have a limited impact on the vehicle CO2 emissions resulting from the pavement condition contribution to rolling resistance. CONCLUSIONS AND RECOMMENDATIONS: Existing models linking pavement condition to rolling resistance and hence vehicle emissions are not broadly applicable to the use phase of road pavement LCA and further research is necessary before a widely-used methodology can be defined. The methods of modelling and the methodological assumptions need to be transparent in the analysis of the impact of the pavement surface condition on fuel consumption, in order to be interpreted by decision makers and implemented in an LCA framework. This will be necessary before product category rules (PCR) for pavement LCA can be extended to include the use phase.

Oil price uncertainty and corporate carbon performance: An international investigation.

Drawing on legitimacy theory and stakeholder theory, this study examines whether oil price uncertainty (OPU) affects corporate carbon performance (CCP) in the international context. Based on data extracted from CDP (previously known as the Carbon Disclosure Project), World Bank, and Thomson Reuters Eikon databases, the study's sample consists of 9074 firm-year observations over the period 2011-2018 for all non-financial multinational companies invited to take part in the CDP questionnaire. Using an ordinary least squares regression model, we identify a strong relationship between OPU and carbon emissions performance. Our findings are robust to a battery of sensitivity tests, all of which support our original results. This study contributes new knowledge regarding the influence of OPU on CCP. The results will be of interest to investors and policymakers as they provide a useful basis for understanding OPU and its impact on CCP to promote better decision-making.

Estimating soil N2O emissions induced by organic and inorganic fertilizer inputs using a Tier-2, regression-based meta-analytic approach for U.S. agricultural lands.

Consistent methods are essential for generating country and region-specific estimates of greenhouse gas (GHG) emissions used for reporting and policymaking. The estimates of direct N2O emissions from U.S. agricultural soils have primarily relied on the use of emission factors (EFs, Tier-1) and process-based models (Tier-3). However, Tier-1 estimates are relatively crude while Tier-3 calculations can be costly. This work addressed this gap by developing a Tier-2, regression-based approach by leveraging a meta-database containing 1883 field N2O observations together with environmental and management covariates from 139 studies. Our results estimated higher monthly soil N2O emissions (N2Om, kg N/ha) during the growing season (0.38) than the fallow period (0.15), highlighting the importance of considering measurement periods when utilizing meta-databases for analyzing N2O drivers. Significantly different N2Om were found for tillage practices (conventional > no-till: 0.42 > 0.27), fertilizer type (liquid > solid manure: 0.55 > 0.32), and soil texture (fine > coarse: 0.36 > 0.22). The comparisons of the influence of crop type and rotation, water management, and soil order on N2O emissions are complicated by regional data availability and interactions among different factors. Additionally, the finding that N2O emissions reported based on area (N2Om), N input rate (EF), or yield can alter treatment rankings underscores the need to establish transparent criteria for rewarding or discouraging regionally-based management practices using N2O metrics. Finally, we show how General Linear Models (GLMs) can be used to estimate country and regional Tier-2 N2Om using a suite of covariates. Our GLMs identified tillage, water management, N input type and rate, soil properties, and elevation as the most influential covariates for the conterminous U.S. The limited accuracy of regional-scale GLMs, however, suggests the need to further improve the quality and availability of GHG and covariate data through concerted efforts in data collection.

High exogenous humus inhibits greenhouse gas emissions from steppe lakes.

Although freshwater lakes are considered to be an important source of greenhouse gas (GHG) emissions, the potential driving mechanisms of such emissions are not well understood, especially in steppe lakes. In this study, the GHG emission characteristics in Hulun Lake Basin, including Hulun Lake, Beier Lake, Wulannuoer Lake, and their surrounding watersheds were investigated. The average methane (CH4) and nitrous oxide (N2O) emission fluxes released from rivers were 67.84 ± 20.53 and 0.11 ± 0.04 µg m-2·min-1, which were larger than those of lakes, with values of 28.60 ± 13.02 and 0.06 ± 0.02 µg m-2·min-1, respectively. Conversely, the average carbon dioxide (CO2) emission flux from lakes (1816.58 ± 498.98 µg m-2·min-1) was higher than that of rivers of (1795.41 ± 670.49 µg m-2·min-1). The water in Hulun Lake Basin was rich in organic matter and had a high chemical oxygen demand (COD). Three-dimensional fluorescence combined with a parallel factor analysis (3D-EEM-PARAFAC) demonstrated that the organic matter was composed of four humus types (from Component 1 (C1) to Component 4 (C4)), of which, C1 and C4 were terrestrial humus. The fluorescence index (FI) and humification index (HIX) indicated that the organic matter in the water was mainly imported from exogenous humus. The GHG emission fluxes were negatively correlated with these four components, indicating that GHG emissions were mainly affected by the organic matter source and components, and humus was the most important factor that inhibited GHG emissions in steppe lakes. However, the GHG emission flux was relatively high in some areas of the lake, especially in areas with high nutrient levels or where algal blooms occurred, as evidenced by the significantly positive correlations with total nitrogen (TN), total phosphorous (TP), and chlorophyll-a (chl-a) (p < 0.01). The algae-derived organic matter simulated the decomposition of refractory humus, thus, promoting GHG emissions. These findings are crucial for accurately evaluating the GHG emission fluxes, understanding the carbon cycle, and proposing future management strategies for steppe lakes.

Analysing driving factors of India's transportation sector CO2 emissions: Based on LMDI decomposition method.

India is the world's third-largest carbon dioxide (CO2) emitter, with the transportation sector accounting for most of this emission. Using the logarithmic-mean Divisia index (LMDI) decomposition method and Tapio decoupling, this study examines the driving factors and their relationship with economic growth for the Indian transportation sector. Transportation-related energy consumption is decomposed into six factors. From 2001 to 2020, CO2 emissions from the Indian transportation sector increased from 155.9 Mt to 368.2 Mt. Roadways produce 88% of all CO2 emissions. Energy systems, economic advancement, and population scale increase CO2 emissions, whereas energy performance and transportation form decrease. Transport advancement demonstrates both tendencies intermittently. CO2 emissions from Indian transportation exhibit a weak decoupling. The increasing demand for vehicles, reliance on conventional fuel, and increase in energy consumption indicate a positive correlation with the increase in the nation's CO2 emissions, while the transition from coal to electric locomotives and the increased use of electric vehicles offset the increase in emissions. In short, the government should update strategic sustainable transport policy measures and emphasize renewable energy. This study will assist policymakers in formulating robust sustainable transportation policies.

Spatial-temporal evolution of the relationship between agricultural material inputs and agricultural greenhouse gas emissions: experience from China 2003-2018.

Agricultural materials input (fertilizer and pesticide, etc.), together with straw burning, rice planting, and livestock breeding, constitute the sources of agricultural greenhouse gas (GHG) emissions. However, most related studies have discussed the total amount of agricultural GHG emissions or the role of straw burning and rice planting in agricultural GHG emissions and few studies on agricultural GHG emissions from Agricultural materials. Based on the data of 31 provinces in China from 2003 to 2018, this paper explored the evolution process of agricultural GHG emissions from Agricultural materials. Our research turned up some interesting findings. For example, firstly, Agricultural materials play an increasingly important role in agricultural GHG emissions. Agricultural GHG emissions due to Agricultural materials account for an increasing proportion of the total agricultural GHG emissions. Secondly, there are regional differences in the evolution trend of agricultural GHG emissions caused by agricultural materials. Especially after the urbanization rate broke through the critical line of 50% around 2010 in China.

Potential application of urease and nitrification inhibitors to mitigate emissions from the livestock sector: a review.

Human activities have caused an increase in greenhouse gas emissions, resulting in climate change that affects many factors of human life including its effect on water and food quality in certain areas with implications for human health. CH4 and N2O are known as potent non-CO2 GHGs. The livestock industry contributes to direct emissions of CH4 (38.24%) and N2O (6.70%) through enteric fermentation and manure treatment, as well as indirect N2O emissions via NH3 volatilization. NH3 is also a secondary precursor of particulate matter. Several approaches have been proposed to address this issue, including dietary management, manure treatment, and the possibility of inhibitor usage. Inhibitors, including urease and nitrification inhibitors, are widely used in agricultural fields. The use of urease and nitrification inhibitors is known to be effective in reducing nitrogen loss from agricultural soil in the form of NH3 and N2O and can further reduce CH4 as a side effect. However, the effectiveness of inhibitors in livestock manure systems has not yet been explored. This review discusses the potential of inhibitor usage, specifically of N-(n-butyl) thiophosphoric triamide, dicyandiamide, and 3,4-dimethylpyrazole phosphate, to reduce emissions from livestock manure. This review focuses on the application of inhibitors to manure, as well as the association of these inhibitors with health, toxicity, and economic benefits.

How can process-based modeling improve peat CO2 and N2O emission factors for oil palm plantations?

Oil palm plantations on peat and associated drainage generate sizeable GHG emissions. Current IPCC default emission factors (EF) for oil palm on organic soil are based on a very limited number of observations from young plantations, thereby resulting in large uncertainties in emissions estimates. To explore the potential of process-based modeling to refine oil palm peat CO2 and N2O EFs, we simulated peat GHG emissions and biogeophysical variables over 30 years in plantations of Central Kalimantan, Indonesia. The DNDC model simulated well the magnitude of C inputs (litterfall and root mortality) and dynamics of annual heterotrophic respiration and peat decomposition N2O fluxes. The modeled peat onsite CO2-C EF was lower than the IPCC default (11 Mg C ha-1 yr-1) and decreased from 7.7 ± 0.4 Mg C ha-1 yr-1 in the first decade to 3.0 ± 0.2 and 1.8 ± 0.3 Mg C ha-1 yr-1 in the second and third decades of the rotation. The modeled N2O-N EF from peat decomposition was higher than the IPCC default (1.2 kg N ha-1 yr-1) and increased from 3.5 ± 0.3 kg N ha-1 yr-1 in the first decade to 4.7-4.6 ± 0.5 kg N ha-1 yr-1 in the following ones. Modeled fertilizer-induced N2O emissions were minimal and much less than 1.6% of N inputs recommended by the IPCC in wet climates regardless of soil type. Temporal variations in EFs were strongly linked to soil C:N ratio and soil mineral N content for CO2 and fertilizer-induced N2O emissions, and to precipitation, water table level and soil NH4+ content for peat decomposition N2O emissions. These results suggest that current IPCC EFs for oil palm on organic soil could over-estimate peat onsite CO2 emissions and underestimate peat decomposition N2O emissions and that temporal variation in emissions should be considered for further improvement of EFs.

Ecological footprints of environmental resources for agricultural production in Iran: a model-based study.

A modeling system was used to calculate the resource footprints (land, water, nutrients, energy, fuel, electricity, and carbon) on a large scale in agricultural production systems (Iran as a case study), and this report is an introduction of this modeling system for future studies. Under irrigated conditions, the highest land footprint was observed in pulses and oil grains (0.6 ha t-1). The lowest water footprints were found in silage corn (300 m3 t-1), and the highest water footprints were observed in oil grains (4525 m3 t-1). The highest footprints of nitrogen were observed in maize (31.7 kg t-1), wheat (30.9 kg t-1), and oil grains (30.4 kg t-1), and the lowest value belonged to production of sugar crops (2.6 kg t-1). Most of the energy, fuel, electricity, and greenhouse gas (GHG) emissions were occurred under irrigated cropping systems compared with the rainfed systems. Under irrigated conditions, the highest footprints of energy, fuel, and electricity and GHG emissions occurred in the production of oil grains, and their values were 24397 MJ t-1, 161 L t-1, 1195 kWh t-1, and 1699 kg CO2eq. t-1, respectively. In general, wheat production in Iran has the highest cost in terms of resource use (water, elements, energy, and carbon) compared with the other plant products. Livestock and poultry products (especially red meat) also had the highest ecological footprint among the products.

Greenhouse gas emissions in sludge ultrasonication followed by anaerobic digestion processes.

This paper presents the greenhouse gas (GHG) emissions during ultrasonication of sludge and anaerobic digestion (AD) of the ultrasonicated sludge using mass-energy balance. Computation of the net energy (energy recovered - energy input) revealed that high solids concentration with low sonication specific energy provides positive net energy. Moreover, the GHG emissions can be minimised at low sonication specific energy input and high solids concentration compared to that of the control without sonication. Increase in temperature of sludge during sonication will reduce the energy input required for raising the sludge temperature to AD temperature and thus decreases the GHG emissions. With energy recovery from the methane produced in AD, the total GHG emissions can further be reduced, lower than that without energy recovery from methane.

Biological Crusts to Increase Soil Carbon Sequestration: New Challenges in a New Environment.

The major priority of research in the present day is to conserve the environment by reducing GHG emissions. A proposed solution by an expert panel from 195 countries meeting at COP 21 was to increase global SOC stocks by 0.4% year-1 to compensate for GHG emissions, the '4 per 1000' agreement. In this context, the application of biocrusts is a promising framework with which to increase SOC and other soil functions in the soil-plant continuum. Despite the importance of biocrusts, their application to agriculture is limited due to: (1) competition with native microbiota, (2) difficulties in applying them on a large scale, (3) a lack of studies based on carbon (C) balance and suitable for model parameterization, and (4) a lack of studies evaluating the contribution of biocrust weathering to increase C sequestration. Considering these four challenges, we propose three perspectives for biocrust application: (1) natural microbiome engineering by a host plant, using biocrusts; (2) quantifying the contribution of biocrusts to C sequestration in soils; and (3) enhanced biocrust weathering to improve C sequestration. Thus, we focus this opinion article on new challenges by using the specialized microbiome of biocrusts to be applied in a new environment to counteract the negative effects of climate change.