Assessment of regional greenhouse gas emission from beef cattle production: A case study of Saskatchewan in Canada

Assessment of urban greenhouse gas emissions towards reduction planning and low-carbon city: a case study of Montreal, Canada

Greenhouse gases (GHGs) can be produced from a broad range of anthropogenic activities at different spatial and temporal scales. In particular, emissions from urban area are an import source of GHGs. City is a complicated system consisting of various component and processes. Efforts have been made to reduce urban GHG emissions. However, there is a lack of available methods for effective assessment of such emissions. Many urban sources and factors which can influence the emissions are still unknown. In the present study, the GHG emissions from municipal activities was assessed. A model for the assessment of urban GHG emissions was developed. Based on the collected data, a case study was conducted to evaluate urban GHG emissions. The comprehensive assessment included the emissions from transportation, electricity consumption, natural gas, waste disposal, and wastewater treatment. There was a variation for GHG emissions from these sectors in different years. This study provided a new approach for comprehensive evaluation of urban GHG emissions. The results can help better understand the emission process and identify the major emission sources.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40068-024-00341-y.

Future prediction of biogas potential and CH4 emission with boosting algorithms: the case of cattle, small ruminant, and poultry manure from Turkey

Animal waste can be converted into a renewable energy source using biogas technology. This process has an impact on greenhouse gas emissions and is a sustainable source of energy for countries. It can reduce the effects of climate change and protect the planet for future generations. Tier1 and tier2 approaches are commonly used in the literature to calculate emissions factors. With boosting algorithms, this study estimated each animal category's biogas potential and CH4 emissions (tier1 and tier2 approach) for 2004-2021 in all of Turkey's provinces. Two different scenarios were created in the study. For scenario-1, the years 2020-2021 were predicted using data from 2004 to 2019, while for scenario-2, the years 2022-2024 were predicted using data from 2004 to 2021. According to the scenario-1 analysis, the eXtreme Gradient Boosting Regressor (XGBR) algorithm was the most successful algorithm with an R2 of 0.9883 for animal-based biogas prediction and 0.9835 and 0.9773 for animal-based CH4 emission predictions (tier1 and tier2 approaches) for the years 2020-2021. When the mean absolute percentage error was evaluated, it was found to be relatively low at 0.46%, 1.07%, and 2.78%, respectively. According to the scenario-2 analysis, the XGBR algorithm predicted the log10 values of the animal-based biogas potential of five major cities in Turkey for the year 2024, with 11.279 for Istanbul, 12.055 for Ankara, 12.309 for Izmir, 11.869 for Bursa, and 12.866 for Antalya. In the estimation of log10 values of CH4 emission, the tier1 approach yielded estimates of 3.080, 3.652, 3.929, 3.411, and 3.321, respectively, while the tier2 approach yielded estimates of 1.810, 2.806, 2.757, 2.552 and 2.122, respectively.

Salinity causes widespread restriction of methane emissions from small inland waters

Inland waters are one of the largest natural sources of methane (CH4), a potent greenhouse gas, but emissions models and estimates were developed for solute-poor ecosystems and may not apply to salt-rich inland waters. Here we combine field surveys and eddy covariance measurements to show that salinity constrains microbial CH4 cycling through complex mechanisms, restricting aquatic emissions from one of the largest global hardwater regions (the Canadian Prairies). Existing models overestimated CH4 emissions from ponds and wetlands by up to several orders of magnitude, with discrepancies linked to salinity. While not significant for rivers and larger lakes, salinity interacted with organic matter availability to shape CH4 patterns in small lentic habitats. We estimate that excluding salinity leads to overestimation of emissions from small Canadian Prairie waterbodies by at least 81% ( ~ 1 Tg yr-1 CO2 equivalent), a quantity comparable to other major national emissions sources. Our findings are consistent with patterns in other hardwater landscapes, likely leading to an overestimation of global lentic CH4 emissions. Widespread salinization of inland waters may impact CH4 cycling and should be considered in future projections of aquatic emissions.

Promoting Cross-Regional Integration of Maritime Emission Management: A Euro-American Linkage of Carbon Markets

Reducing greenhouse gas emissions from maritime transport is an urgent topic. Some regional emissions trading systems (ETSs), buoyed by the globalized market-based measures (MBMs) plan of the International maritime organization, have initially assessed the feasibility of including maritime emissions under compliance obligations. However, including maritime emissions (which are interjurisdictional) in the existing ETSs is controversial, and globalized maritime MBMs remain elusive. Therefore, this study designed a joint bilateral maritime carbon market (BMCM) model based on the European ETS (EU-ETS) and Quebec ETS (QC-ETS). The carbon costs, speed optimization, and marginal abatement costs of three container routes under BMCM were analyzed. The results show that this Euro-American linkage achieves adequate emission coverage on specific routes and generates acceptable carbon costs for charterers. This study yields a positive result for the equal division of ETSs' exercising competence in cross-regional maritime transport and provides evidence for sector-specific ETS links based on quantitative analysis.

Modeling of energy and emissions from animal manure using machine learning methods: the case of the Western Mediterranean Region, Turkey

In Turkey, facilities for the use of biomass resources in energy production are increasing, and new conversion facilities are commissioned every year to provide environmentally friendly energy production. Therefore, reliable energy potential estimates are needed. In this study, the animal manure-based-biogas potentials of Antalya, Isparta, and Burdur provinces in the Western Mediterranean Region of Turkey were calculated. Here, special information on cattle, small ruminants, and poultry, and animal age, number, and manure amount information were used in detail. In addition, carbon dioxide emissions, coal, electricity, and thermal energy, methane emission values with the Tier 1 and Tier 2 approaches were calculated and predicted by machine learning algorithms. To determine the model with the best results, machine learning algorithms support vector machine (SVM), multi-layer perceptron (MLP), and linear regression (LR) were used, and hyper-parameter optimization was performed. According to the results of biogas potential, CO₂ emission, electricity production, and thermal energy estimations SVM models are seen as the best models with R² = 0.999. When the coal amount estimation is examined, the LR models produce better results than SVM and MLP with R² = 0.997. In the estimation of CH₄ using the Tier 1 approach, the MLP model can perform the best estimation with R² = 0.977. In the CH₄ modeling obtained using the Tier 2 approach, the LR models were superior to the other models with the performance value of R² = 0.962.

Environmental advantages of coproducing beef meat in dairy systems

Beef meat, one of the more environmentally costly animal-based foods, can be produced in two general ways, as the main product on specialised farms or as a co-product on dairy farms. In this study, two cases (a semi-confinement dairy farm (A) and a pasture-based dairy farm (B)) have been analysed by means of LCA to evaluate the environmental impacts associated with the coproduction of beef meat. In both cases, purchased feed production was found to be the main cause of environmental impacts in most of the categories considered. Additionally, cow emissions to air were the main contributor for the global warming category. Comparing the two dairy systems, notably lower environmental impacts were obtained for B in 13 of the 18 categories analysed. Regarding CF, 8.10 and 8.88 kg CO₂eq/kg LW were obtained for A and B, respectively. These CF values were within the wide range found in the literature for beef meat (1.2-42.6 kg CO₂eq/kg LW). Beef calves and cull cows are an important output of dairy farming, so that coproduction enables milk and meat with lower CF and associated environmental impacts to be obtained. In addition, the variability of the data found in literature and the lack of LCA studies based on real data for beef meat coproduced on dairy farms evidence the importance of in-depth study of this interesting topic.

An experimental and modeling study on the penetration of spilled oil into thawing frozen soil

Oil spills are significant environmental accidents that have significant impacts on environmental and ecological health. Spill pollution in the cold regions may pose a particular challenge. To achieve a fast response, the oil transport mode such as penetration should be well understood. In this study, the oil penetration behavior in thawing frozen soil at different temperatures and water contents were investigated. The results showed the penetration behavior of spilled oil in the thawing frozen soil and the influence of salinity level. The modified Green-Ampt model could simulate the penetration process well especially with high water content, relatively cold temperature, and slow thawing rate. This study reveals the new features of oil penetration behavior and distribution patterns in thawing frozen soil under different conditions. Hence, it is of significant importance to support the rapid response measures and reduce the contamination of oil spill accidents in cold regions.

Impact from the evolution of private vehicle fleet composition on traffic related emissions in the small-medium automotive city

Understanding the emission characteristics in the evolution of private vehicle fleet composition has become a key issue to be addressed to develop appropriate emission mitigation strategies in transportation sector. In this study, the influence of such evolution on on-road emissions was investigated based on a comprehensive dataset encompassing vehicle fleet composition, demographic, economic, and energy features from a representative small-medium automotive city in North America. The decoupling analysis was carried out to assess the dynamic linkage between environmental pressure exerted by the transportation sector and economic growth at both city level and national level in North America. We also developed an approach that supports the long-term traffic-related air pollutant prediction and investigated the potential influence on urban air quality. A sharp upward trajectory was observed in the quantity of SUVs from 2001 to 2018, gradually replacing the dominance of the quantity of four-door cars. There was a significant shift in the GHG emissions emitted from vehicle types used for passenger transport: emissions from SUVs and trucks rose by 374.0% and 69.3%, respectively, whereas emissions from four-door cars, two-door cars, station wagons, and vans all decreased. The changes in vehicle composition, along with the steady trend in GHG emissions from private fleet and decrease in on-road air pollutant concentrations found in Regina, were a response to the establishment of federal fuel economy standards and improved fuel economy. Relative decoupling was observed in aggregate for Regina and Canada in most of the years while both experienced economic downturns and increases in environmental pressure in the form of emissions from 2014 to 2015. The predicted results also demonstrate the high capability of XGboost machine learning algorithm in predicting on-road air pollutant concentrations of CO, PM_2.5, and NO_X.

Cleanup of oiled shorelines using a dual responsive nanoclay/sodium alginate surface washing agent

Oil spills may affect ecosystems and endanger public health. In this study, we developed a novel and dual responsive nanoclay/sodium alginate (NS) washing fluid, and systematically evaluated its application potential in oiled shoreline cleanup. The characterization results demonstrated that sodium alginate combined with nanoclay via hydrogen bonds, and was inserted into the interlayer spacing of nanoclay. Adding sodium alginate reduced surface and interfacial tensions, while increasing the viscoelasticity of the washing fluid. Batch experiments were conducted to investigate oil removal performance under various conditions. Additionally, the factorial design analysis showed that three single factors (temperature, oil concentration, and salinity), and two interactive effects (temperature/salinity; and oil concentration/HA) displayed significant effects on the oil removal efficiency of the NS washing fluid. Compared to the commercial surfactants, the NS composite exhibited satisfactory removal efficiencies for treating oily sand. Green materials-stabilized Pickering emulsion can potentially be used for oil/water separation. The NS washing agent displayed excellent pH- and Ca²⁺- responsiveness, generating transparent supernatants with low oil concentration and turbidity. Our work opens an interesting avenue for designing economical, high performance, and green washing agents.

A change is gonna come: will traditional meat production end?

Recently, the world has faced environmental disasters mainly due to global warming. One of the main reasons for global temperature imbalances is the greenhouse gases (GHG) that soar the atmosphere's heat. The major aim of the current study is to explore whether the livestock population is the main contributor to GHG emission through econometric estimations. In this study, we examine the impact of livestock population with other explanatory variables-GDP per capita, Economic Complexity Index (ECI), ecological balance, and total patent applications-over GHG emission of 25 countries responsible for 76% of GHG emission between 1990 and 2017. To investigate the relationship of variables, Fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are used, as well as panel causality. Also, the relationship is examined by using the responsiveness scores (RS) approach. The empirical results reveal that all variables have a causal relationship with GHG emission. GDP per capita, ECI, and livestock population enhance the GHG emission whereas square of GDP per capita and ecological balance decline the environmental degradation. The paper demonstrates that the environmental Kuznets curve is valid and supports the literature. Lastly, the RS estimation results reveal that the livestock population is causing higher GHG emissions for all countries in the analysis, contrary to other independent variables. Governments should promote carbon-neutral meat production facilities instead of traditional beef farms to live in a more sustainable world. In the future, countries that invest in research and development (R&D) for less emission meat production will have a comparative advantage in the sustainable international meat market.

Assessing the regional biogenic methanol emission from spring wheat during the growing season: A Canadian case study

As a volatile organic compound existing in the atmosphere, methanol plays a key role in atmospheric chemistry due to its comparatively high abundance and long lifetime. Croplands are a significant source of biogenic methanol, but there is a lack of systematic assessment for the production and emission of methanol from crops in various phases. In this study, methanol emissions from spring wheat during the growing period were estimated using a developed emission model. The temporal and spatial variations of methanol emissions of spring wheat in a Canadian province were investigated. The averaged methanol emission of spring wheat is found to be 37.94 ± 7.5 μg·m^-2·h^-1, increasing from north to south and exhibiting phenological peak to valley characteristics. Moreover, cold crop districts are projected to be with higher increase in air temperature and consequent methanol emissions during 2020-2099. Furthermore, the seasonality of methanol emissions is found to be positively correlated to concentrations of CO, filterable particulate matter, and PM₁₀ but negatively related to NO₂ and O₃. The uncertainty and sensitivity analysis results suggest that methanol emissions show a Gamma probabilistic distribution, and growth length, air temperature, solar radiation and leafage are the most important influencing variables. In most cases, methanol emissions increase with air temperature in the range of 3-35 °C while the excessive temperature may result in decreased methanol emissions because of inactivated enzyme activity or increased instant methanol emissions due to heat injury. Notably, induced emission might be the major source of biogenic methanol of mature leaves. The results of this study can be used to develop appropriate strategies for regional emission management of cropping systems.

Spatiotemporal analysis of land use pattern and stream water quality in southern Alberta, Canada

Alberta has over 70% of total irrigated land in Canada and 13 irrigation districts are mainly located along the rivers in southern Alberta. The runoff and irrigation return flow can carry excess nutrients, pesticides, and sediments, which adversely affect the river water quality. In the present study, the comprehensive spatiotemporal analysis of land use pattern and stream water quality in southern Alberta was conducted. The water quality monitoring on the South Saskatchewan River watershed within Alberta showed that most water quality indicators did not significantly change between 2003 and 2017. Land use maps demonstrated significant urban expansion and cropland decline in the study area from 2005 to 2015, while the irrigation area increased. Correlation analysis and redundancy analysis revealed that cropland, built-up land, and native grassland were three land use types that were positively correlated with water quality indicators. Stronger correlations between nitrogen concentration and built-up land were found in dry seasons compared with wet seasons. According to the results of cluster analysis, higher water quality indicator concentrations could be observed in groups with a higher proportion of cropland and built-up land. Significant relationships between land use patterns and water quality were found in this study, which demonstrated that further investigation is needed to identify the sources of water pollutants at a smaller scale.

Environmental and biodiversity effects of different beef production systems

Agricultural livestock production ranks among the most environmental impactful industry sectors at the global level, and within the livestock sector, beef production accounts for a large proportion of environmental damage. Beef production in Alpine mountain regions, such as in South Tyrol (Italy), is a small, but increasing agricultural sector. Thus, the aim of this study was to examine the environmental impact of different organic and conventional beef production systems in South Tyrol and to compare their environmental impact and effect on biodiversity under Alpine production conditions. Live cycle assessment (LCA) approach was used and 1 kg of live weight (LW) was chosen as functional unit (FU). Global warming potential (GWP, kg CO₂-eq), acidification potential (AP, g SO₂-eq), eutrophication potential (EP, g PO₄-eq), non-renewable energy use (NRE, MJ-eq), land occupation (LO, m² organic land/year) and biodiversity damage potential (BDP) expressed in potential disappeared fraction (PDF) were investigated. The study involved 18 beef cattle farms in the South Tyrolean region: Conventional calf-fattening farms (CCF = 6), organic suckler cow farms (SCF = 6), and conventional heifer/ox fattening farms (HOF = 6). The CCF system showed a higher environmental impact compared to SCF and HOF systems for all impact categories (P < 0.05). Between the organic and the conventional system (SCF and HOF), no significant differences (P > 0.05) were found for most of the considered impact categories (means ± SEM per FU): GWP: 19.8 vs 17.1 ± 4.2 kg CO_2-eq, AP: 11.4 vs 9.3 ± 4.7 g SO₂-eq, EP: 4.1 vs 2.8 ± 1.2, NRE: 21.9 vs 13.8 ± 7 MJ-eq, SCF and HOF respectively. Only for LO (70.8 vs 44.1 ± 17.7 m² organic/y, P < 0.01, SCF and HOF respectively) and the effect on BDP (-1.93 vs -0.85 ± 0.35, PDF, P < 0.01, SCF and HOF respectively) differences between organic and conventional production methods could be revealed. The study showed that beef cattle husbandry in the Alpine area has a satisfactory environmental performance. In particular, the systems studied showed a positive impact in terms of biodiversity.

The Research Progress of the Influence of Agricultural Activities on Atmospheric Environment in Recent Ten Years: A Review

In recent years, the industrial emission of air pollution has been reduced via a series of measures. However, with the rapid development of modern agriculture, air pollution caused by agricultural activities is becoming more and more serious. Agricultural activities can generate a large amount of air pollutants, such as ammonia, methane, nitrogen oxides, volatile organic compounds, and persistent organic pollutants, the sources of which mainly include farmland fertilization, livestock breeding, pesticide use, agricultural residue burning, agricultural machinery, and agricultural irrigation. Greenhouse gases emitted by agricultural activities can affect regional climate change, while atmospheric particulates and persistent organic pollutants can even seriously harm the health of surrounding residents. With the increasing threat of agricultural air pollution, more and more relevant studies have been carried out, as well as some recommendations for reducing emissions. The emissions of ammonia and greenhouse gases can be significantly reduced by adopting reasonable fertilization methods, scientific soil management, and advanced manure treatment systems. Regarding pesticide use and agricultural residues burning, emission reduction are more dependent on the restriction and support of government regulations, such as banning certain pesticides, prohibiting open burning of straw, and supporting the recycling and reuse of residues. This review, summarizing the relevant research in the past decade, discusses the current situation, health effects, and emission reduction measures of agricultural air pollutants from different sources, in order to provide some help for follow-up research.

Quantifying construction waste reduction through the application of prefabrication: a case study in Anhui, China

Due to the rapid pace of urbanization in China, there has been a significant increase in construction work, which has resulted in the generation of more waste. Reducing the waste at source is the most efficient way to reduce its negative impacts, and prefabrication is a construction method that does exactly that. Since prefabricated construction generates less waste compared to conventional cast-in-situ construction, it is being promoted by the Chinese government. This study investigates the benefits of prefabrication and quantifies the percentage of construction waste reduction through its application in China. It does so by using a 26-storey concrete-brick residential building as a case study, and by conducting uncertainty analysis with Oracle Crystal Ball simulation software to assess the reduction of waste when using prefabricated components in place of cast-in-situ elements. Simulation results demonstrated that the waste generation rate for in-situ timber formwork and masonry work was 10.52 and 4.77 kg/m² respectively, and that the use of prefabricated components reduced those figures by 36.04% and 25.53% respectively. This study quantifies the benefits of prefabrication as a method for reducing the generation of construction waste in China. Not only would extensive use of prefabrication decrease the cost related to construction waste management in China, but it could also mitigate the environmental and social impacts of construction waste globally.

Assessing the impact of COVID-19 pandemic on urban transportation and air quality in Canada

The global outbreak and spread of COVID-19 had a significant impact on the environment of urban areas. This study aimed to provide a new insight into the urban transportation and air pollutant emission of representative Canadian cities impacted by this pandemic. The consumption of urban transportation fuel was analyzed and the corresponding CO₂ emissions was evaluated. The changes in urban traffic volume and air pollutant concentrations before and after the outbreak of this pandemic was investigated. Due to the lockdown after the outbreak of COVID-19, the domestic consumption of motor gasoline and estimated CO₂ emissions from urban vehicles in Canada has continuously decreased with a lowest level in April 2020, and rebounded in May 2020. It will still take a long time to recover to pre-pandemic levels because of the upcoming second wave of pandemic and further change. The Air Quality Health Index (AQHI), level of urban congestion and concentration level of NO₂ and CO had strong relevance with the COVID-19 period while SO₂ did not show significant relation. The comprehensive analysis of changing fuel consumptions, traffic volume and emission levels can help the government assess the impact and make corresponding strategy for such a pandemic in the future.

Exploring the use of cellulose nanocrystal as surface-washing agent for oiled shoreline cleanup

Surface-washing agents are an option to enhance the removal of oil spilled or stranded on shorelines. The use of nanocellulose-based nanofluid as a surface-washing agent was studied by investigating its reactivity and effectiveness. Salinity was found to be the most influencial factor to facilitate oil removal with the nanofluids. Cations from salt can promote the adsorption of nanocellulose on the oil/water interface by reducing the surface charges. The experimental results revealed the nanocellulose could be effective at low concentrations but an excess of nanocellulose hindered oil removal due to an increase in fluid viscosity. A miscibility model was applied to verify this finding in a thermodynamics context. The biotoxicity tests showed that nanocellulose-based nanofluid did not have negative effects on algae growth and introducing nanocellulose into an oiled culture medium can actually mitigate the toxicity of the oil on algae. A comparison in removal efficiency with other surfactants demonstrated the potential value for shoreline cleanup due to the superior effectiveness of nanocellulose-based nanofluids. Overall, a nanocellulose has a high potential for application as a surface-washing agent for shoreline cleanup due to the low cost, low toxicity, and high efficiency.

Investigation into the oil removal from sand using a surface washing agent under different environmental conditions

Spilled oil frequently reaches the shorelines and affects coastal biota and communities. The application of surface washing agents is an important shoreline cleanup technique that can help remove stranded oil from substrate surfaces with the advantages of high removal efficiency, low toxicity, and strong economic viability. In this study, the investigation into the oil removal from contaminated sand using a surface washing agent under variable environmental conditions was conducted. A preliminary test was conducted to obtain the optimal combination of operating factors of surface washing agent-to-oil ratio (SOR) 2:1, mixing speed 150 rpm, and mixing time 30 min. The results of single-factor experiments showed that high temperature and humic acid concentration of flush water contributed to the performance of a surface washing agent, while salinity and kaolinite concentration could inhibit its performance. The factorial analysis revealed the main effects of temperature and salinity, and the interactive effects of temperature and salinity as well as salinity and humic acid concentration that were significant to the washing efficiency of the surface washing agent. In addition, the comprehensive assessment of a surface washing agent from the aspects of toxicity, detergency, dispersion properties, and field trials was conducted. The results have significant implications for future application of surface washing agents in the shoreline cleanup.