A study on wildfire impacts on greenhouse gas emissions and regional air quality in South of Orléans, France.

Wildfire events are increasing globally which may be partly associated with climate change, resulting in significant adverse impacts on local, regional air quality and global climate. In September 2020, a small wildfire (burned area: 36.3 ha) event occurred in Souesmes (Loir-et-Cher, Sologne, France), and its plume spread out over 200 km on the following day as observed by the MODIS satellite. Based on measurements at a suburban site (∼ 50 km northwest of the fire location) in Orléans and backward trajectory analysis, young wildfire plumes were characterized. Significant increases in gaseous pollutants (CO, CH4, N2O, VOCs, etc.) and particles (including black carbon) were found within the wildfire plumes, leading to a reduced air quality. Emission factors, defined as EF (X) = ∆X/∆CO (where, X represents the target species), of various trace gases and black carbon within the young wildfire plumes were determined accordingly and compared with previous studies. Changes in the ambient ions (such as ammonium, sulfate, nitrate, chloride, and nitrite in the particle- and gas- phase) and aerosol properties (e.g., aerosol water content, aerosol pH) were also quantified and discussed. Moreover, we estimated the total carbon and climate-related species (e.g., CO2, CH4, N2O, and BC) emissions and compared them with fire emission inventories. Current biomass burning emission inventories have uncertainties in estimating small fire burned areas and emissions. For instance, we found that the Global Fire Assimilation System (GFAS) may underestimate emissions (e.g., CO) of this small wildfire while other inventories (GFED and FINN) showed significant overestimation. Considering that it is the first time to record wildfire plumes in this region, related atmospheric implications are presented and discussed.

Life cycle assessment of greenhouse gas emissions for various feedstocks-based biochars as soil amendment.

Anthropogenic greenhouse gas (GHG) emissions are a major factor influencing climate change. The application of biochar as a soil amendment may be an effective way to reduce GHG emissions. Life cycle assessment (LCA) is widely used to assess the impact of biochar as a soil amendment on GHG emissions. The methodology is effective in assessing the impacts of the various stages of the biochar life cycle on GHG emissions. However, because of the diversity of biochar types, it is difficult to summarize the regularity of biochar life cycle impacts on GHG emissions. This paper summarizes the pathways of biochar's effect on GHG emissions and in-depth analyzes the mechanism of biochar's influence on GHG emissions from the perspective of biochar properties. Finally, the review comprehensively analyzes the effects of different types of biochar feedstock on GHG emissions at the stages of feedstock pretreatment, preparation, and application of the life cycle. The conclusions are as follows: (1) Biochar affects GHG emissions in three ways: feedstock supply, pyrolysis process, and application process. (2) The impact of biochar on GHG emissions is influenced by a combination of the physicochemical properties of biochar. (3) Biochar has a positive impact (feedstock pretreatment stage and preparation stage) or a negative impact (application stage) on life cycle GHG emissions. (4) The carbon sequestration capacity of biochar varies by feedstock type. The ranking of carbon sequestration capacity is waste wood biochar (WWB) > crop straw biochar (CSB) > livestock manure biochar (LMB) > sewage sludge biochar (SSB).

Exploring low-carbon mulching strategies for maize and wheat on-farm: Spatial responses, factors and mitigation potential.

Mulching strategies - including plastic film mulching (FM) and straw mulching (SM) - can enhance crop yields while affecting multiple greenhouse gas (GHG) fluxes. However, most of currently published site-based studies only focus on a certain gas, resulting in an inability to spatially integrated understanding of changes in agricultural global warming potential (GWP) and greenhouse gas intensity (GHGI) caused by mulching across China. Thus, we developed an optimal model considering crop type, meteorology, soil and management variables by four machine learning methods, namely support vector machine, multilayer perceptron, random forest, and gradient boosting machine (GBM). Then we mapped the relative changes in yield and GHG fluxes caused by mulching strategies. The GBM model had the best simulation capability for yield and GHGs in China. Our result showed that FM increased yield in maize (25 %) and wheat (19 %), while SM respectively increased by 14 % and 11 %. Among the relative changes due to mulching strategies, yield and N2O emissions were mainly influenced by soil fertility and soil properties, CH4 uptakes and CO2 emissions were more affected by environmental factors. GWP in maize and wheat average increased by 40 % under FM, while SM decreased GWP by 14 % and 2 %, respectively. Besides, FM average increased GHGI in maize and wheat by 17 % and 9 %, and SM decreased GHGI by 22 % and 12 %, respectively. Spatially, FM reduced maize GWP on 19 % of cropland, while SM reduced maize and wheat GWP on 71 % and 64 % of cropland, respectively. Soil pH was significantly correlated with ΔGHGI in maize and wheat. Our analysis not only estimated for the first time the spatial effects of mulching strategies across China, but also systematically analyzes the agricultural carbon emission mitigation potential of mulching strategies, which promote the development of low-carbon agriculture based on locally appropriate mulching strategies.

Crop-livestock-forestry systems as a strategy for mitigating greenhouse gas emissions and enhancing the sustainability of forage-based livestock systems in the Amazon biome.

Intensification of livestock systems becomes essential to meet the food demand of the growing world population, but it is important to consider the environmental impact of these systems. To assess the potential of forage-based livestock systems to offset greenhouse gas (GHG) emissions, the net carbon (C) balance of four systems in the Brazilian Amazon Biome was estimated: livestock (L) with a monoculture of Marandu palisade grass [Brachiaria brizantha (Hochst. ex A. Rich.) R. D. Webster]; livestock-forestry (LF) with palisade grass intercropped with three rows of eucalyptus at 128 trees/ha; crop-livestock (CL) with soybeans and then corn + palisade grass, rotated with livestock every two years; and crop-livestock-forestry (CLF) with CL + one row of eucalyptus at 72 trees/ha. Over the four years studied, the systems with crops (CL and CLF) produced more human-edible protein than those without them (L and LF) (3010 vs. 755 kg/ha). Methane contributed the most to total GHG emissions: a mean of 85 % for L and LF and 67 % for CL and CLF. Consequently, L and LF had greater total GHG emissions (mean of 30 Mg CO2eq/ha/year). Over the four years, the system with the most negative net C balance (i.e., C storage) was LF when expressed per ha (-53.3 Mg CO2eq/ha), CLF when expressed per kg of carcass (-26 kg CO2eq/kg carcass), and LF when expressed per kg of human-edible protein (-72 kg CO2eq/kg human-edible protein). Even the L system can store C if well managed, leading to benefits such as increased meat as well as improved soil quality. Moreover, including crops and forestry in these livestock systems enhances these benefits, emphasizing the potential of integrated systems to offset GHG emissions.

Legacy effects of slag and biochar application on greenhouse gas emissions mitigation in paddy field: A three-year study.

The utilization of slag and biochar in croplands has been proposed as a management approach to mitigate greenhouse gas (GHG) emissions, specifically methane (CH4) and nitrous oxide (N2O), from agricultural fields. However, there is limited understanding of the long-term effects of single and combined applications of slag and biochar on GHG emissions in rice paddy fields. We investigated the legacy effects of one-year applications of slag, biochar, and slag+biochar on CH4 and N2O emissions, physicochemical properties, and rice yields during a three-year period (2016-2018) in southeast China. Over the study period, the application of slag reduced CH4 emissions by 24 %, biochar by 45 %, and the combined application of slag+biochar by 44 %. Across the study period, slag, biochar, and slag+biochar applications resulted in respective N2O emissions increases of 78 %, 63 %, and 80 %. Methane emissions contributed to approximately 70 % of the global warming potential (GWP) in the paddy field, which was reduced by 20 % with biochar application and by 15 % with the combined application of slag+biochar. Additionally, the total rice yield in the slag, biochar, and slag+biochar treatments increased by 7 %, 5 %, and 10 %, respectively, compared to the control group. Based on our findings, we recommend the combined application of slag+biochar as a sustainable rice management strategy to effectively reduce GHG emissions from paddy fields while enhancing yield production.

Influences of wildfire on the forest ecosystem and climate change: A comprehensive study.

Wildfires have complex impacts on forests, including changes in vegetation, threats to biodiversity, and emissions of greenhouse gases like carbon dioxide, which exacerbate climate change. The influence of wildfires on animal habitats is particularly noteworthy, as they can lead to significant changes in native environments. The extent of these alterations in species and habitats plays a crucial role in shaping forest ecology. Drought, disease, insect infestations, overgrazing, or their combined effects can amplify the negative effects on specific plant genera and entire ecosystems. In addition to the immediate consequences of plant mortality and altered community dynamics, forest fires have far-reaching implications. They often increase flowering and seed production, further influencing ecological communities. However, one concerning trend is the decline in the diversity of forest biological species within fire-affected areas. Beyond their ecological impacts, wildfires emit substantial quantities of greenhouse gases and fine particulates into the atmosphere, triggering profound changes in climate patterns and contributing to global warming. As vegetation burns during these fires, the carbon stored within is released, rendering large forest fires detrimental to biodiversity and the emission of CO2, a significant contributor to global warming. Measuring the global impact of wildfires on ecological communities and greenhouse gas emissions has become increasingly vital. These research endeavors shed light on the intricate relationships and feedback loops linking wildfires, ecosystem inhabitants, and the evolving climate landscape.

Responses of soil greenhouse gas emissions to soil mesofauna invasions and its driving mechanisms in the alpine tundra: A microcosm study.

Climate change is resulting in significant modifications of the altitudinal patterns of soil fauna in mountains, leading to their upward invasion and alteration of soil ecological processes. However, the effects of soil greenhouse gas (GHG) emissions from soil mesofauna invasion and their driving mechanisms have not been clearly understood. To address this knowledge gap, we simulated a soil mesofauna invasion from an Erman's birch forest (EB) to the alpine tundra (AT) of the Changbai Mountain in Northeast China. Four treatments were established: no soil mesofauna (S0), native species (SN), invasive species (SI), and invasive species superposed native species (SS). We conducted a 79-day microcosm experiment, utilizing gas chromatography and high-throughput sequencing, to explore the variations in soil greenhouse gas emissions and their driving factors. Results showed that the cumulative CO2 emissions under SN, SI, and SS, compared with S0, increased by 34.13 %, 73.93 %, and 107.64 % and cumulative N2O emissions increased by 59.05 %, 101.18 %, and 183.88 %, respectively. Compared to SN, the cumulative emissions of CO2 and N2O increased by 29.89 % and 26.31 % under SI and by 54.91 % and 78.59 % under SS, respectively. The impacts of invasive species and native species on greenhouse gases were not a simple additive effect. Abiotic (soil variables) and biotic (soil mesofauna and microbial diversity) factors explained 37.76 % and 44.41 % of the total variations in CO2 and N2O emissions, respectively, in which NH4+-N and C: N ratios contributed the largest variations. The contribution of soil mesofauna diversity to the variations in CO2 and N2O emissions was higher than that of microbial diversity. The bacterial network graph density was correlated with soil CO2 and N2O emissions. Our findings highlight that soil mesofauna invasions increased GHG emissions, and these variations were predominantly explained by biotic rather than abiotic factors.

Carbon price and firm greenhouse gas emissions.

Drawing on the recent enthusiasm in the carbon markets, I examine the impact of carbon prices on firm greenhouse gas (GHG) emissions. Using a sample of 1591 firms from 23 European countries, I demonstrate that an increase in carbon price decreases corporate GHG. At hypothesized higher carbon pricing levels, I document that the effect of pricing on corporate GHG emissions is negative. The negative impact of high carbon prices manifests in other harmful gases such as sulphur and volatile organic compounds (VOCs). In evaluating how the various phases of the EU emission trading scheme have affected firm greenhouse gas emissions, I show that the negative effect of pricing became pronounced in Phase 3 of the EU ETS. The findings from this study are robust to alternative econometric specifications and further sample selection criteria.

The pandemic effect on GHG emission variation at the sub-national level and translation into policy opportunities.

Greenhouse gas (GHG) emissions inventories are commonly compiled at country level to monitor national progress towards nationally or internationally agreed targets. While they can support national climate change mitigation strategies, accounting for the intra-national heterogeneity of a country can draw different conclusions directly linked to the socio-economic and environmental sub-national context. This means that more refined and accurate policies and mitigation strategies can be designed when supported by GHG inventories at sub-national scale. The differences between sub-national territorial emissive behavior can be revealed by subjecting different territories to the same stress factors. A complete GHG emissions inventory, based on the Intergovernmental Panel on Climate Change (IPCC) Guidelines, is compiled for three diverse administrative territories, in terms of scale, socio-economic contexts, and environmental conditions. By selecting three diverse sub-national contexts belonging to the same national territory - Italy - the analysis provides highly detailed information on the emissive status and behavior and delivers insights that national inventories fail to provide. The COVID-19 pandemic is considered as a stress factor; therefore, the reference years are 2019 and 2020 during which GHG emissions are detected. The study will test the capacity of sub-national GHG emission inventories, compiled by scaling the IPCC methodology to the sub-national level, to detect such differences through the lens of the pandemic. This allows obtaining detailed information and linking the pandemic effect to the GHG emissions of particular activities, which can inspire effective sub-national context-specific mitigation actions. Furthermore, we show that environmental and economic metrics are not as strictly coupled as they would appear at national level.

Effects of integrated nutrient management and urea deep placement on rice yield, nitrogen use efficiency, farm profits and greenhouse gas emissions in saline soils of Bangladesh.

Soil salinity is one of the major yield-limiting factors in the coastal ecosystems of Bangladesh. An efficient fertilizer management practice and selection of appropriate crop cultivars could play a crucial role in improving yield and promoting low-carbon agriculture across saline soils. A two-year multi-location field experiment was conducted during the Boro (dry) season (December-April) to investigate the effects of fertilizer management and rice cultivar selection on rice yield, economic viability, and global warming potential (GWP) in coastal saline soils of Bangladesh. The study included seven fertilizer treatments with varying nitrogen rates and sources, as well as two rice cultivars (BRRI dhan67 and BRRI dhan88). The results showed that integrated nutrient management-2 (INM-2) significantly (p < 0.05) increased rice yield and nitrogen use efficiency compared to other treatments for both BRRI dhan67 and BRRI dhan88. Similarly, INM-2 gave a higher return on fertilizer investment and marginal benefit-cost ratio than other treatments in both locations and under both cultivars. BRRI dhan67 significantly (p < 0.05) increased rice yield relative to BRRI dhan88 by 21 % and 52 % at the BRRI farm and Kaliganj in Satkhira, respectively. The cost-dominant analysis excluded BRRI dhan88 and all fertilizer treatments, except urea deep placement (UDP) and INM-2, from consideration in both locations. Consequently, INM-2 and UDP proved to be economically viable in both locations, with INM showing a higher marginal rate of return than UDP in BRRI dhan67. In terms of environmental sustainability, UDP significantly (p < 0.05) reduced GWP and yield-scaled emissions of CH4 by 31 % and 38 % without causing yield loss compared to INM-2. Similarly, BRRI dhan67 significantly (p < 0.05) reduced GWP and yield-scaled emissions of CH4 by 5 and 22 % compared to BRRI dhan88. These findings suggest that selecting salt-tolerant rice cultivars and implementing appropriate fertilizer management practices can enhance economic profitability, ensure food security, and mitigate the adverse effects of climate change in coastal saline soils.

Assessment of governmental strategies for sustainable environment regarding greenhouse gas emission reduction under uncertainty.

Since greenhouse gas emissions (GHGE) directly impact climate change that affects the environment, human health, society, and ecosystems, the reduction of GHGE is one of the essential actions for the sustainability of the environment. To reduce global GHGE, the United Nations has defined strategies at three levels: government, private, and public. Choosing between these strategies is a difficult process since there are relationships and contradictions among them. The process also includes uncertainties due to some reasons, such as lack of information, social structure, decision makers' hesitancy, and imprecision in the collected data. In this paper, a hierarchically structured methodology based on a decision-making procedure is proposed for the evaluation of the governmental strategies determined to decide the best strategies by integrating expert knowledge and a literature review. For this aim, interpretative structural modeling, cognitive mapping, and inference systems are integrated as a two-stage decision-making methodology based on fuzzy sets to address uncertainties and imprecision in the evaluation of government strategies for GHGE reduction in Türkiye. Based on the results of the first stage, "Transportation" is determined as the most influential sector for GHGE mitigation. In the second stage, strategies of the transportation sector are assessed and ranked. "Promoting the significant public health benefits of low-carbon policies, including increased public transportation and non-motorized mobility" is determined as the most appropriate transportation strategy for the governmental action plan regarding the climate change reduction objective. This paper contributes to applying knowledge and experiences from the current environmental characteristics and social fields to the strategic decision of the GHGE reduction area, to streamline its assessment process, provide human-centered solutions, and accelerate governmental actions.

Environmental impact assessment of a combined bioprocess for hydrogen production from food waste.

With the growth of population and the development of economy, the food waste (FW) and energy shortage issues are getting great attentions. In this study, the environmental performance of a biorefinery of enzymatic hydrolysis and fermentation for hydrogen production from FW (FW-H2) was investigated by life cycle assessment (LCA) in terms of greenhouse gas (GHG) emissions and non-renewable energy use (NREU). It was found that the gas compression, electricity and FW transport were the major environmental hotspots in the FW-H2 process. The GHG emissions of 10.1 kg CO2 eq and NREU of 104 MJ were obtained from per kg hydrogen production through the whole process. The environmental impacts of the FW-H2 process were lower than the conventional processes for hydrogen production, such as steam methane reforming and electrolysis with grid. Sensitivity analysis demonstrated that the efforts in environmental hotspots, especially in gas compression, could result in the improvement of environmental impacts of the FW-H2 process. The GHG emissions and NREU could reduce to 89.2 % and 89.4 % with a 20 % reduction of energy consumption for gas compression. Different allocation methods (economic allocation, mass allocation, no allocation and system expansion method) applied for LCA analysis could provide a significant influence of environmental impacts in the FW-H2 process. The results obtained from this study could lead to further research into resource recycling from waste and would ultimately contribute to the development of circular economy.

Climatic zone effects of non-native plant invasion on CH4 and N2O emissions from natural wetland ecosystems.

Plant invasion can significantly alter the carbon and nitrogen cycles of wetlands, which potentially affects the emission of greenhouse gases (GHGs). The extent of these effects can vary depending on several factors, including the species of invasive plants, their growth patterns, and the climatic conditions prevailing in the wetland. Understanding the global effects of plant invasion on the emission of methane (CH4) and nitrous oxide (N2O) is crucial for the climate-smart management of wetlands. Here, we performed a global meta-analysis of 207 paired case studies that quantified the effect of non-native plant invasion on CH4 and N2O emissions in tropical/sub-tropical (TS) and temperate (TE) wetlands. The average emission rate of CH4 from the TS wetlands increased significantly from 337 to 577 kg CH4 ha-1 yr-1 in areas where native plants had been displaced by invasive plants. Similarly, in TE wetlands, the emission rates increased from 211 to 299 kg CH4 ha-1 yr-1 following the invasion of alien plant species. The increase in CH4 emissions at invaded sites was attributed to the increase in plant biomass, soil organic carbon (SOC), and soil moisture (SM). The effects of plant invasion on N2O emissions differed between TS and TE wetlands in that there was no significant effect in TS wetlands, whereas the N2O emissions reduced in TE wetlands. This difference in N2O emissions between climate zones was attributed to the depletion of NH4+ and NO3- in soils and the lower soil temperature in temperate regions. Overall, plant invasion increased the global net CH4 emissions from natural wetlands by 10.54 Tg CH4 yr-1. However, there were variations in CH4 emissions across different climatic zones, indicated by a net increase in CH4 emissions, of 9.97 and 0.57 Tg CH4 yr-1 in TS and TE wetlands, respectively. These findings highlight that plant invasion not only strongly stimulates the emission of CH4 from TS wetlands, but also suppresses N2O emissions from TE wetlands. These novel insights immensely improve our current understanding of the effects of climatic zones on biogeochemical controlling factors that influence the production of greenhouse gases (GHGs) from wetlands following plant invasion. By analyzing the specific mechanisms by which invasive plants affect GHG emissions in different climatic zones, effective strategies can be devised to reduce GHG emissions and preserve wetland ecosystems.

Greenhouse gas emissions from Daihai Lake, China: Should eutrophication and salinity promote carbon emission dynamics?

Greenhouse gases (GHGs) emitted or absorbed by lakes are an important component of the global carbon cycle. However, few studies have focused on the GHG dynamics of eutrophic saline lakes, thus preventing a comprehensive understanding of the carbon cycle. Here, we conducted four sampling analyses using a floating chamber in Daihai Lake, a eutrophication saline lake in Inner Mongolia Autonomous Region, China, to explore its carbon dioxide (CO2) and methane (CH4) emissions. The mean CO2 emission flux (FCO2) and CH4 emission flux (FCH4) were 17.54 ± 14.54 mmol/m2/day and 0.50 ± 0.50 mmol/m2/day, respectively. The results indicated that Daihai Lake was a source of CO2 and CH4, and GHG emissions exhibited temporal variability. The mean CO2 partial pressure (pCO2) and CH4 partial pressure (pCH4) were 561.35 ± 109.59 µatm and 17.02 ± 13.45 µatm, which were supersaturated relative to the atmosphere. The regression and correlation analysis showed that the main influencing factors of pCO2 were wind speed, dissolved oxygen (DO), total nitrogen (TN) and Chlorophyll a (Chl.a), whereas the main influencing factors of pCH4 were water temperature (WT), Chl.a, nitrate nitrogen (NO3--N), TN, dissolved organic carbon (DOC) and water depth. Salinity regulated carbon mineralization and organic matter decomposition, and it was an important influencing factor of pCO2 and pCH4. Additionally, the trophic level index (TLI) significantly increased pCH4. Our study elucidated that salinity and eutrophication play an important role in the dynamic changes of GHG emissions. However, research on eutrophic saline lakes needs to be strengthened.

Structurally stable but functionally disrupted marine microbial communities under a future climate change scenario: Potential importance for nitrous oxide emissions.

The blue mussel Mytilus edulis is a widespread and abundant bivalve species along the North Sea with high economic and ecological importance as an engineer species. The shell of mussels is intensively colonized by microbial organisms that can produce significant quantities of nitrous oxide (N2O), a potent greenhouse gas. To characterize the impacts of climate change on the composition, structure and functioning of microbial biofilms on the shell surface of M. edulis, we experimentally exposed them to orthogonal combinations of increased seawater temperature (20 vs. 23 °C) and decreased pH (8.0 vs. 7.7) for six weeks. We used amplicon sequencing of the 16S rRNA gene to characterize the alpha and beta diversity of microbial communities on the mussel shell. The functioning of microbial biofilms was assessed by measuring aerobic respiration and nitrogen emission rates. We did not report any significant impacts of climate change treatments on the diversity of mussel microbiomes nor on the structure of these communities. Lowered pH and increased temperature had antagonistic effects on the functioning of microbial communities with decreased aerobic respiration and N2O emission rates of microbial biofilms in acidified seawater compared to increased rates in warmer conditions. An overriding impact of acidification over warming was finally observed on N2O emissions when the two factors were combined. Although acidification and warming in combination significantly reduced N2O biofilm emissions, the promotion of aquaculture activities in coastal waters where shellfish do not normally occur at high biomass and density could nonetheless result in unwanted emissions of this greenhouse gas in a near future.

Greenhouse gas emissions from bio-based growing media: A life-cycle assessment.

In this study, using an LCA approach we explored how bio-based peat alternatives (wood fiber, compost, and hydrochar based on willow and degassed fiber from agricultural waste) and their mixtures (75 % peat with 25 % peat alternative) as growing media (GM) for plant production in Denmark may provide benefits for reducing greenhouse gas emissions compared to peat. To perform this, foreground data (collected via personal communication and literature) was used together with background data from Ecoinvent V3.8. The chosen functional unit was 1 m3 of GM and the system boundary was from cradle to use as GM. The global warming potential of all the peat alternatives showed significant reduction, varying between 89 and 109 % compared to peat. When incorporating 25 % of each alternative with peat, the climate footprint was reduced by 16 to 33 % compared to pure peat. Thus, there are large climate prospects in replacing peat with bio-based alternatives, and the results underlines the relevance of being able to increase the proportion of the bio-based components in their mixtures with peat beyond the 25 % and towards 100 % replacement. The effectiveness of peat substitutes in term of reducing the CO2 emissions is affected by choice of the feedstock, their processing method and emissions of their end-use.

Adding Corbicula fluminea altered the effect of plant species diversity on greenhouse gas emissions and nitrogen removal from constructed wetlands in the low-temperature season.

Plant species diversity is crucial in greenhouse gas emissions and nitrogen removal from constructed wetlands (CWs). However, previous studies have overlooked the impact of benthos on cumulative greenhouse gas emissions during the low-temperature season in CWs. In this study, we established 66 vertical flow CWs with three levels of species richness (1, 2, and 4 species) and eleven species compositions. The Corbicula fluminea was added or not added at each diversity level and monitored greenhouse gas emissions and effluent nitrogen concentration. Our findings indicated that (1) in microcosms without C. fluminea, high species richness significantly increased effluent nitrogen concentrations (NO3--N, NH4+-N, and TIN), but plant species richness did not affect cumulative CH4, N2O, and CO2 emissions. The presence of Hemerocallis fulva significantly increased cumulative CO2 emissions, while the presence of Iris tectorum significantly increased effluent nitrogen (NO3--N and TIN) concentrations and cumulative N2O emissions; (2) in microcosms with C. fluminea, the lowest cumulative CH4 emissions occurred when there were two species, but plant species richness did not affect cumulative CO2 and N2O emissions. The presence of H. fulva significantly increased cumulative CH4 emissions, while the presence of Reineckea carnea significantly increased effluent nitrogen (NO3--N, NH4+- N, TIN) concentrations; (3) at the same diversity level, the addition of C. fluminea significantly increased cumulative CH4 and N2O emissions, as well as effluent nitrogen concentrations. These results demonstrate that C. fluminea alters the effect of plant species diversity on cumulative greenhouse gas emissions and nitrogen removal from CWs during the low-temperature season. We recommend using a two-species mixture to reduce greenhouse gas emissions. However, we caution against using plant compositions with H. fulva or I. tectorum for effective wastewater treatment and greenhouse gas reduction in CWs.

A systematic review of life-cycle GHG emissions from intensive pig farming: Accounting and mitigation.

Pork accounts for approximately 35 % of the global meat supply, with approximately 747 million tons of CO2e greenhouse gas (GHG) emissions annually. To meet the increasing demand for pork, intensive farming is becoming the priority rearing system owing to its higher productivity. Given the climate transformation ambitions of the pig industry but the lack of knowledge and data, we conducted a systematic review of studies published in the period of 2010-2022 from a life-cycle perspective, with a focus on greenhouse gas emissions accounting and mitigation. The significant variations in systematic harmonized global warming intensities (GWIs) can be primarily attributed to differences in accounting approaches, activity data, technologies and geographical conditions. To understand more, we broke down the entire life cycle and revealed the underlying reasons for modelling mechanisms and data from the main emitters (e.g., feeding, pig rearing, and manure management). These findings are expected to support and improve the transparency, consistency, and comprehensiveness of life-cycle GHG emissions accounting in pig farming. Potential mitigation measures were also reviewed and discussed to provide insights to support the sustainable development of the pig industry.

Development of an assessment-based planting structure optimization model for mitigating agricultural greenhouse gas emissions.

Optimization of crop structure is an efficient way to reduce greenhouse gas (GHGs) from agriculture production. However, carbon footprint have rarely been incorporated into previous planting structure optimization models due to the challenges of assessing the spatial and temporal distribution of agricultural carbon footprint for multiple crops in irrigated districts. In addition, previous planting structure models suffered from strong subjectivity in objective function determination, and the obtained non-dominated solution set offered difficulties to decision-makers in selecting specific implementation options. To fill such gaps, an integrated accounting-assessment-optimization-decision making (AAODM) approach was proposed, which remedies the shortcomings of previous crop planting structure optimization models in carbon footprint mitigation, and overcomes the subjectivity of objective function determination and the difficulty in selecting specific implementation options. Firstly, life cycle assessment (LCA) method was used to account for the multi-year agricultural carbon footprints of multiple crops in the irrigation district. The optimization objective functions of planting structure optimization models can then be determined based on the assessment method of carbon footprint influencing factors. Next, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was used to generate a non-dominated solution set of the optimization model. The optimal planting structure can be finally obtained based on decision making methods by determining the maximum harmonic mean (HM) and knee points (KPs) of the non-dominated solution set. The developed AAODM approach was then applied to a case study of agricultural crop management in Bayan Nur City, China. The results showed that the level of economic development was a key factor influencing the increase in carbon footprint in Bayan Nur City over the past 20 years. The regulation of the level of economic development would significantly influence the agricultural carbon footprint in Bayan Nur City. Moreover, two optimal crop cultivation patterns were provided for decision-makers by selecting solutions from the Pareto front with decision making methods. The comparison results with other methods showed that the solutions obtained by NSGA-II were superior to MOPSO in terms of carbon reduction. The developed AAODM approach for agricultural GHG mitigation could help agricultural production systems in achieving low carbon emissions and high efficiency.