Source Of Greenhouse Gases Research Articles

An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

CO2 Measurement under Different Pressure and Vibration Conditions Using Tunable Diode Laser Absorption Spectroscopy

The greenhouse effect resulting from fuel combustion has drawn growing attention, and CO2 emissions from fossil fuel power stations are one of the main sources of greenhouse gases. It is crucial to monitor the concentration of CO2 in the flue gas ducts of these stations. However, pressure and vibration caused by the combustion of boilers make the measurement of CO2 in flue gas ducts extremely challenging. In this study, tunable diode laser absorption spectroscopy (TDLAS) combined with Wave Modulation Spectroscopy (WMS) was employed to measure the concentration of CO2 under different pressure and vibration conditions in the laboratory. The absorption line of CO2 at the wavenumber 6357.38 cm−1 was recorded under varying pressure conditions ranging from 0 to 1.4 atm, acceleration conditions ranging from 0 to 7.7 m/s2, and a combination of both. Firstly, a negative linear correlation was found between the pressure and the amplitude of the second harmonic, with a maximum relative error of 4.645% observed at a pressure of 1.4 atm. Secondly, the maximum acceleration that the system can withstand was determined to be 7.3 m/s2, as it was not possible to provide a sufficiently low fitting error at higher accelerations. For the combined effects of the pressure and vibration, a dramatic increase in the relative error of amplitude can be observed within the acceleration range of 5.0~6.0 m/s2 while under the pressure conditions of 0.6 atm, 1.0 atm, and 1.4 atm. Moreover, the maximum endurable acceleration decreases with the increase in pressure, which infers that effective measurements can be achieved when the acceleration is below 5 m/s2 within the pressure range of 0~1.4 atm. This suggests that TDLAS combined with WMS possesses a potential for online measuring of CO2 concentrations in flue gas ducts within a certain acceleration range. This work can provide some insights for stable gas detection using TDLAS under varied pressure and vibration conditions.

Soil organic matter on arid saline-alkali land drives greenhouse gas emissions from artificial and natural grasslands in different directions

Reducing greenhouse gas (GHG) emissions and mitigating the pace of global warming are crucial to achieving a balance between economic development and ecological protection. However, research on GHG emissions from different types of artificial grasslands is limited. This study aimed to elucidate the dynamics of GHG emission fluxes in three types of artificial grasslands and natural saline meadow grassland (NG). Meteorological and soil data were collected to determine the correlations between GHG fluxes and environmental variables. All grasslands were sources of CO2 and N2O. Artificial grasslands were sinks of CH4, whereas NG was a CH4 source. FCO2 was the main source of GHGs in grasslands. The average emissions of FCO2 and FN2O in artificial grasslands were higher than those in NG. Soil temperature had a positive effect on GHG emissions in all grasslands and soil organic matter content was the main factor affecting all grassland GHG fluxes.

Quantifying and Comparing Greenhouse Gas Emissions in Monsoon Rice Production: A Comprehensive Analysis of Transplanting and Broadcasting Sowing Methods in Myanmar

Introduction Rice is a staple food, an economic crop, and the second-highest source of greenhouse gas (GHG) emissions in the agricultural sector in Myanmar. To develop the rice sector in a sustainable way, this study aimed to determine the comparative GHG emissions between the two major sowing methods used in monsoon rice production. Methods Next, comparative GHG emissions analysis was done by using the Student t-test. This study first quantified GHG emissions from land preparation to straw burning by using emission factors for agricultural inputs and the formulation, default values, and scaling factors of a carbon footprint calculator customized for rice products (CF-Rice). Results Soil and water management was the largest contributor among the management practices in monsoon rice production and accounted for 64.8% of the total GHG emissions. At 4,479.5 kg CO2 eq. ha-1, GHG emissions from the broadcasting (BC) method were significantly higher than those from the transplanting (TP) method. Conclusion Therefore, the TP method is a better sowing technique than the BC method for reducing GHG emissions without reducing grain yield.

Effect of Alternate Wetting and Drying on the Emission of Greenhouse Gases from Rice Fields on the Northern Coast of Peru

The cultivation of rice is one of the main sources of greenhouse gas (GHG) emissions due to continuously flooded irrigation (CF), which demands large volumes of water. As an alternative solution, alternate wetting and drying (AWD) irrigation has been developed as a water-saving strategy. This study was conducted at the Experimental Agricultural Station (EEA) in Vista, Florida, in the Lambayeque region located on the northern coast of Peru. Thus, it was analyzed the effect of AWD irrigation at different depths (5, 10, and less than 20 cm below the surface) compared to CF control on methane (CH4) and nitrous oxide (N2O) emissions and rice grain yield. AWD treatments reduced CH4 emissions by 84% to 99% but increased N2O emissions by 66% to 273%. In terms of Global Warming Potential (GWP), the AWD10 treatment demonstrated a 77% reduction and a Water Use Efficiency (WUE) of 0.96, affecting only a 2% decrease in rice grain yield, which ranged between 11.85 and 14.01 t ha−1. Likewise, this study provides sufficient evidence for the adoption of AWD irrigation as a strategy for the efficient use of water resources and the mitigation of GHG emissions in rice cultivation in the study area, compared to continuous flooded irrigation.

Greenhouse Gases Emissions by Energy Production and Waste Disposal

Biomass is very important source for energy production in Latvia [1]. Wood biomass – firewood, wood chips and pellets are the main part of biomass, because 54,7 % of the state area is covered by forests. Also other kinds of biomass are playing significant role in the heat and electricity production. Such kinds of biomass are various agricultural and food production residues, livestock breeding buy-products, sewage sludge, organic part of household and industrial wastes, etc. Approximately 1/3 of energy is used for household in Latvia. The significant part of energy is produced in local heating facilities. They by large part of greenhouse gases (GHG) are produced in household. In the same time gases from the municipal waste disposals are also significant source of GHG. The results of measurements and evaluation of GHG emissions from biomass burning in household boilers and municipal solid waste disposals are reported in the present work. The calculations of GHG emissions are conducted by using software and data from Latvian Environment, Geology and Meteorology Centre (LEGMC).

Greenhouse gas emissions and their trends over the last 3 decades across Africa

Abstract. A key goal of the Paris Agreement (PA) is to reach net-zero greenhouse gas (GHG) emissions by 2050 globally, which requires mitigation efforts from all countries. Africa's rapidly growing population and gross domestic product (GDP) make this continent important for GHG emission trends. In this paper, we study the emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in Africa over 3 decades (1990–2018). We compare bottom-up (BU) approaches, including United Nations Convention Framework on Climate Change (UNFCCC) national inventories, FAO, PRIMAP-hist, process-based ecosystem models for CO2 fluxes in the land use, land use change and forestry (LULUCF) sector and global atmospheric inversions. For inversions, we applied different methods to separate anthropogenic CH4 emissions. The BU inventories show that, over the decade 2010–2018, fewer than 10 countries represented more than 75 % of African fossil CO2 emissions. With a mean of 1373 Mt CO2 yr−1, total African fossil CO2 emissions over 2010–2018 represent only 4 % of global fossil emissions. However, these emissions grew by +34 % from 1990–1999 to 2000–2009 and by +31 % from 2000–2009 to 2010–2018, which represents more than a doubling in 30 years. This growth rate is more than 2 times faster than the global growth rate of fossil CO2 emissions. The anthropogenic emissions of CH4 grew by 5 % from 1990–1999 to 2000–2009 and by 14.8 % from 2000–2009 to 2010–2018. The N2O emissions grew by 19.5 % from 1990–1999 to 2000–2009 and by 20.8 % from 2000–2009 to 2010–2018. When using the mean of the estimates from UNFCCC reports (including the land use sector) with corrections from outliers, Africa was a mean source of greenhouse gases of 262221863239 Mt CO2 eq. yr−1 from all BU estimates (the subscript and superscript indicate min–max range uncertainties) and of +263717615873 Mt CO2 eq. yr−1 from top-down (TD) methods during their overlap period from 2001 to 2017. Although the mean values are consistent, the range of TD estimates is larger than the one of the BU estimates, indicating that sparse atmospheric observations and transport model errors do not allow us to use inversions to reduce the uncertainty in BU estimates. The main source of uncertainty comes from CO2 fluxes in the LULUCF sector, for which the spread across inversions is larger than 50 %, especially in central Africa. Moreover, estimates from national UNFCCC communications differ widely depending on whether the large sinks in a few countries are corrected to more plausible values using more recent national sources following the methodology of Grassi et al. (2022). The medians of CH4 emissions from inversions based on satellite retrievals and surface station networks are consistent with each other within 2 % at the continental scale. The inversion ensemble also provides consistent estimates of anthropogenic CH4 emissions with BU inventories such as PRIMAP-hist. For N2O, inversions systematically show higher emissions than inventories, on average about 4.5 times more than PRIMAP-hist, either because natural N2O sources cannot be separated accurately from anthropogenic ones in inversions or because BU estimates ignore indirect emissions and underestimate emission factors. Future improvements can be expected thanks to a denser network of monitoring atmospheric concentrations. This study helps to introduce methods to enhance the scope of use of various published datasets and allows us to compute budgets thanks to recombinations of those data products. Our results allow us to understand uncertainty and trends in emissions and removals in a region of the world where few observations exist and where most inventories are based on default IPCC guideline values. The results can therefore serve as a support tool for the Global Stocktake (GST) of the Paris Agreement. The referenced datasets related to the figures are available at https://doi.org/10.5281/zenodo.7347077 (Mostefaoui et al., 2022).

Hydrogen-independent CO2 reduction dominates methanogenesis in five temperate lakes that differ in trophic states.

Emissions of microbially produced methane (CH4) from lake sediments are a major source of this potent greenhouse gas to the atmosphere. The rates of CH4 production and emission are believed to be influenced by electron acceptor distributions and organic carbon contents, which in turn are affected by anthropogenic inputs of nutrients leading to eutrophication. Here, we investigate how eutrophication influences the abundance and community structure of CH4 producing Archaea and methanogenesis pathways across time-resolved sedimentary records of five Swiss lakes with well-characterized trophic histories. Despite higher CH4 concentrations which suggest higher methanogenic activity in sediments of eutrophic lakes, abundances of methanogens were highest in oligotrophic lake sediments. Moreover, while the methanogenic community composition differed significantly at the lowest taxonomic levels (OTU), depending on whether sediment layers had been deposited under oligotrophic or eutrophic conditions, it showed no clear trend in relation to in situ distributions of electron acceptors. Remarkably, even though methanogenesis from CO2-reduction was the dominant pathway in all sediments based on carbon isotope fractionation values, taxonomic identities, and genomes of resident methanogens, CO2-reduction with hydrogen (H2) was thermodynamically unfavorable based on measured reactant and product concentrations. Instead, strong correlations between genomic abundances of CO2-reducing methanogens and anaerobic bacteria with potential for extracellular electron transfer suggest that methanogenic CO2-reduction in lake sediments is largely powered by direct electron transfer from syntrophic bacteria without involvement of H2 as an electron shuttle.

Analysis of vehicle specific power and road grade in a high-altitude city

Vehicles are a major source of atmospheric pollutants and greenhouse gases. Real Driving Emissions (RDE) testing is used to study the real-world effects of parameters that are not considered in laboratory testing but that can influence fuel consumption and vehicle emissions. This paper analyzes the vehicle specific power (VSP) and the effects of positive and negative road slopes on the fuel consumption of a sport utility vehicle (SUV). The vehicle was tested on a route at an altitude of 2750 meters in Riobamba, Ecuador. The circuit design included urban, rural, and highway driving that met the requirements of European Union (EU) Regulation 2018/1832. Low-cost devices were used to record data from the road tests to determine fuel consumption as a function of road slope. VSP+ analysis revealed that there is a good correlation with fuel consumption, with an R2 of 0.86. For road slopes of -6% to +6%, the percentage variation in fuel consumption is linearly correlated (R2 = 0.85) with the slope variations.

Comparative Analysis of Peatland Emission Factors: Unravelling the Need for Standardized Measurement and Reporting

Abstract Peatlands have a crucial role in the global carbon cycle, acting as significant carbon sinks, but become a significant source of greenhouse gas (GHG) emissions when peatlands are drained, and during peat extraction. This article presents a comprehensive overview of peatland ecosystems, emphasizing their classification across various climatic zones and the complex set of different characteristics that determine contribution to GHG emissions. Currently, inconsistencies exist in the definition of emission factors used between countries leading to varied approaches in estimating peatland emissions and posing significant challenges in the comparison and aggregation of global data on peat extraction related GHG. The aim of the study is to analyse the disparities in emission factors and calculation methodologies employed by different countries. Data from national GHG emission reports are submitted under the UNFCCC and the Kyoto Protocol. Emissions report data calculations and emission factors can be based on either nationally determined data or data specified in the IPCC guidelines. Consequently, emission factor data for four countries - Latvia, Finland, Sweden and Germany - are collected and processed, which was compared with IPCC guidelines data. The data was compared by equating units of measurement. The results show there is a pronounced difference between the emission factors of each country, however, all of these factors are lower than the maximum values specified in the IPCC guidelines. The study concludes that emission factors are predetermined differently for each country, and it is not possible to determine the differences among assumptions for parameters included in the specification of the emission factors. The results suggest there is a need for development of a more transparent accounting for emissions with regard to the diverse environmental and anthropogenic factors influencing peatland ecosystems. Factors like composition, depth of peat, water table levels, and local land-use practices further compound this variability in emission accounting. Addressing these challenges is crucial for enhancing the accuracy and reliability of GHG emission reporting under international frameworks like the United Nations Framework Convention on Climate Change and the Kyoto Protocol.

Research on carbon dioxide emission factor characteristics of multi-type heavy-duty vehicles

CO2 emissions from heavy-duty vehicles are an important source of greenhouse gases in the transportation sector. However, there is a lack of in-depth research on the characteristics of CO2 emission factors of multiple types of heavy-duty vehicles. The paper conducts a study on the characteristics of carbon dioxide emission factors of multi-type heavy-duty vehicles, with a focus on tractors, heavy-duty trucks, and dump trucks. A method based on C-WTVC for VSP-Bin interval division is proposed to establish a unified bin interval for heavy-duty vehicles, and calculate the CO2 emission factors of different types of heavy-duty vehicles. The study indicates that the carbon dioxide emission factors of tractors are mainly distributed in suburb and highway intervals. The carbon dioxide emission factors of heavy-duty trucks are distributed across three intervals. The CO2 emission factors of dump trucks are concentrated in suburb intervals.

Role of green hydrogen in the decarbonization of the energy system in Thailand

High dependence on fossil fuels to meet the energy demand is the major source of greenhouse gas (GHG) emissions in Thailand. Decarbonization of the energy system to achieve the pledged climate targets is a challenging task for Thailand. The role of green hydrogen and hydrogen-based technologies in Thailand's energy transition needs to be explored. A bottom-up energy system model developed using AIM/Enduse framework has been used to assess the energy system transformation required with the focus on the role of hydrogen in achieving net zero GHG emissions. A business-as-usual (BAU) scenario and two net zero emissions (NZE) scenarios with low and high-hydrogen use have been assessed. This study finds that GHG emission reduction in the power sector and the transport sector would be the major contributor in achieving net zero emission in 2050 compared to the projected emissions in the BAU level. Energy efficiency improvement in the demand side would lower the electricity consumption compared to the BAU level despite the higher electrification of the end-use technologies. However, the demand to produce green hydrogen in the NZE scenarios would increase the electricity generation in 2050 b y up to 54 % compared to the BAU level. The capacity of electrolyser would reach 50 GW by 2050 in the high hydrogen use scenario. This would require additional solar and wind power capacity of 107 GW and 43 GW, respectively. In addition, it would require 50 million cubic meters of water. Cumulative investments in electrolysers to produce green hydrogen and renewable based power generation during 2031–2050 would be USD 122 billion.

Estimating the GHGs and the MAC of Agricultural Production Systems in China

As the second largest source of greenhouse gas (GHG) emissions, the agricultural system has an arduous task of reducing emissions. There is an urgent need to think about how to achieve the goal of peaking carbon emissions in agricultural production at the lowest cost. This paper applied the Intergovernmental Panel on Climate Change (IPCC) factor method to calculate the GHG emissions of China’s agricultural production systems and deconstruct it into the crop farming and animal husbandry sectors. Input–output indicators based on parametric directional distance functions were constructed to assess the green production efficiency (GPE) of different agricultural sectors and scientifically quantify the marginal abatement costs (MACs) of different GHGs. The results showed the following: (a) During 2000 to 2020, GHG emissions from China’s agricultural production systems averaged 87.73 million tons of CO 2 -eq and showed a fluctuating downward trend. CH 4 emissions accounted for the largest average proportion of 55%, mainly animal enteric fermentation and rice methane emissions. (b) The average level of agricultural GPE in China is 0.79, and 0.76 for crop farming is slightly higher than 0.67 for animal husbandry. (c) The average MAC is 1,861.71 yuan/ton CO 2 -eq, and it is increasing year by year. The shadow price is positively correlated with the efficiency level. The “high-efficiency–low-cost” areas are key areas for agricultural emission reduction, such as Henan and Shandong provinces. Formulate emission reduction strategies according to the characteristics of regional GHG emissions to promote the realization of the “dual carbon” goal of agriculture.

Congestion and Pollutant Emission Analysis of Urban Road Networks Based on Floating Vehicle Data

Global warming caused by greenhouse gas (GHG) is receiving increasingly attention from all over the world, and urban transportation is a significant source of greenhouse gas and pollutant emission. However, the research on traffic state of urban road networks (URNs) based on sparse floating vehicle data (FVD) is insufficient. Therefore, we mainly utilize big data techniques to explore the congestion and pollutant emission of URN with FVD. Firstly, the location of vehicles is identified and matched with the URN. We then grid the FVD and city maps to more accurately identify areas of congestion and emission in later section. Following this, we use the congestion index and K-means clustering algorithm to evaluate the traffic state over time, pollutant emission is calculated based on emission calculation standards and carbon emission is estimated by using the fuel consumption-speed model. The results indicate that congestion and emission are very severe during peak hours (e.g., 8:00 a.m.), particularly in some transportation hub areas, such as high-speed rail stations. During off-peak hours (e.g., 11:00 p.m.), congestion and emission are relatively lower. The negative correlation between congestion index and emission is also revealed. This study provides some practical approaches to more accurately estimate the overall urban traffic state by using sparse traffic data, and may offer support to urban traffic managers in managing traffic congestion and pollutant emissions.

Climate change must be factored into savanna carbon- management projects to avoid maladaptation: the case of worsening air pollution in western Top End of the Northern Territory, Australia

Savanna fires are a major source of greenhouse gas (GHG) and particulate pollution globally. Since mid-2006, an Australian Government carbon offset program has incentivised Northern Territory land managers to undertake early dry-season savanna burning with the aim of reducing late dry-season wildfires and associated GHG emissions. The focus of this study is addressing concern that savanna burning carbon abatement projects are causing worsening air pollution in the city of Darwin. Reconstructed concentrations of daily particulate matter of <2.5 μm (PM2.5) since the 1960s showed since 2000s a worsening in PM2.5 in the early dry season (May, June, July), some improvement in the late dry season (August, September, October) with little overall difference for the whole dry season. Remote-sensing PM2.5 estimates in Darwin were correlated with region-wide PM2.5 estimates during the early dry season. Remote-sensing analysis of area burned and intensity of fires since 2002 showed that savanna carbon projects have shifted burning to the early dry season and caused increases in fire intensity compared with non-project areas. Increased fire intensity appears to follow sharply declining fuel moisture, as well as management effects on carbon project areas, which have possibly undermined the efficacy of savanna burning projects in reducing GHG emissions. More thorough evaluation of underlying assumption of savanna burning carbon abatement in Australia and elsewhere in the world is required to avoid maladaptation, such as over-crediting, smoke pollution, and other environmental harms.

Size matters: Aerobic methane oxidation in sediments of shallow thermokarst lakes

AbstractShallow thermokarst lakes are important sources of greenhouse gases (GHGs) such as methane (CH4) and carbon dioxide (CO2) resulting from continuous permafrost thawing due to global warming. Concentrations of GHGs dissolved in water typically increase with decreasing lake size due to coastal abrasion and organic matter delivery. We hypothesized that (i) CH4 oxidation depends on the natural oxygenation gradient in the lake water and sediments and increases with lake size because of stronger wind‐induced water mixing; (ii) CO2 production increases with decreasing lake size, following the dissolved organic matter gradient; and (iii) both processes are more intensive in the upper than deeper sediments due to the in situ gradients of oxygen (O2) and bioavailable carbon. We estimated aerobic CH4 oxidation potentials and CO2 production based on the injection of 13C‐labeled CH4 in the 0–10 cm and 10–20 cm sediment depths of small (~300 m2), medium (~3000 m2), and large (~106 m2) shallow thermokarst lakes in the West Siberian Lowland. The CO2 production was 1.4–3.5 times stronger in the upper sediments than in the 10–20 cm depth and increased from large (158 ± 18 nmol CO2 g−1 sediment d.w. h−1) to medium and small (192 ± 17 nmol CO2 g−1 h−1) lakes. Methane oxidation in the upper sediments was similar in all lakes, while at depth, large lakes had 14‐ and 74‐fold faster oxidation rates (5.1 ± 0.5 nmol CH4‐derived CO2 g−1 h−1) than small and medium lakes, respectively. This was attributed to the higher O2 concentration in large lakes due to the more intense wind‐induced water turbulence and mixing than in smaller lakes. From a global perspective, the CH4 oxidation potential confirms the key role of thermokarst lakes as an important hotspot for GHG emissions, which increase with the decreasing lake size.

Modeling the Effect of Green Roofs for Building Energy Savings and Air Pollution Reduction in Shanghai

Building energy consumption is an essential source of greenhouse gas (GHG) and air pollution. Green roofs can directly absorb ambient CO2 and remove air pollutants through their vegetation layers, but a limited number of studies have examined their effects on GHG and air pollutant reduction associated with building energy savings, especially in the context of climate change. This research examined the performance of green roofs on CO2 and air pollutant reduction, including SO2, PM2.5, and NOx, through building energy demand savings in Shanghai, China. Climate change mitigation effects were assessed based on the energy consumption of five types of buildings before and after the installation of green roofs under 2020 and 2050 climate conditions, respectively. EnergyPlus software 9.5.0 was applied to simulate hourly energy consumption for different building prototypes with and without green roofs. Green roofs on all building types exhibited positive energy savings on annual, monthly, and diurnal scales, and they can save more energy for most of the building types under the projected 2050 climate condition. Moreover, most of the building energy saved by green roofs came from the Heating, Ventilation, and Cooling (HVAC) systems. In addition, this study discovered that the energy-saving benefits of green roofs vary based on the type of building they were installed on. Green roofs were found to have the largest energy saving on the shopping mall, especially on extremely hot summer days. Finally, a Geographic Information System (GIS)-based approach was developed with the ability to quantify the amount of GHG and air pollutant reduction associated with building energy savings for existing buildings in the Huangpu District of Shanghai. This approach was also utilized to present the spatial distribution of buildings with different levels of suitability to install green roofs by considering their location attributes and air pollutant reduction potential together, which is the major innovation of this research. The purpose of this study is to provide valuable guidance to policy makers regarding the performance of green roofs in building energy-saving and air quality improvement in the urban environment when facing the challenge of climate change, which is essential for urban sustainability.

The ratio but not individual of fragile to refractory DOM affects greenhouse gases release in different trophic level lakes

Inland shallow lakes are recognized as an important source of greenhouse gases (GHGs), and their contribution is expected to increase due to global eutrophication. The generation and release of GHGs involved multiple variables, leading to many uncertain potential factors. This study examined the emission characteristics of GHGs at the water-air interface in 12 shallow lakes categorized into four eutrophic levels in the Yangtze River basin. The average emission rates of CH4, CO2 and N2O were 1.55, 3.43, 18.13 and 30.47 mg m−2 h−1, 4.12, 14.64, 25.11 and 69.84 mg m−2 h−1, and 0.2, 0.25, 0.43 and 0.79 mg m−2 day−1 in the oligotrophic, mesotrophic, eutrophic and hypereutrophic lakes, respectively. There were significant correlations between eutrophic levels and the emission rates of CH4 and CO2 (p < 0.05). Redundancy analysis and Mantel test were conducted to further examine the key factors influencing carbon emissions from eutrophic water. It was found that the presence of algae and nutrients in the overlying water played a crucial role in the release of GHGs, indicating the importance of ecosystem productivity in the carbon budget of the lake. In order to assess the bioavailability of organic matter, a new indicator called R(P/H) was proposed. This indicator represents the ratio of protein and humus-like components, which were obtained through EEMs-PARAFAC modeling. The relationship between R(P/H) and CH4 was found to be exponential (R2 = 0.90). Additionally, R(P/H) showed a linear relationship with CO2 and N2O (R2 = 0.68, R2 = 0.75). Therefore, it is crucial to consider R(P/H) as an important factor in accurately estimating global GHG emission fluxes in the future, especially with advancements in the database.

Development and Optimization of a Chamber System Applied to Maize Net Ecosystem Carbon Exchange Measurements

Net ecosystem carbon exchange (NEE) in agricultural land represents a significant source of global greenhouse gas (GHG) emissions. While there are various tools for measuring NEE in agricultural fields, the chamber method remains the sole tool at the plot scale. In this research, we evaluated the NEE of maize plants at the nodulation stage using the flow-through chamber method. Many existing flow-through chamber systems directly introduce gases, leading to collisions with plants and subsequent turbulence inside the chamber. Turbulence can extend the time required to achieve a steady state. We modified the traditional flow-through chamber design to minimize turbulence in the measurement zone. Our modifications were validated by modeling the chamber and maize plants and by conducting fluid simulation experiments. In the analysis of our comparative field measurements between the two chamber designs, the use of the improved system notably shortened the time required to reach the steady state, increased the measurement frequency, and reduced the influence of changing environmental factors on the readings. Enhancing the measurement frequency is crucial for ensuring long-term accuracy. By reducing turbulence in the chamber, we anticipate improvements in the precision of NEE measurements in agricultural research, which could significantly contribute to an accurate assessment of the global carbon cycle.

Evaluating the Crucial Relationships between Soil Health and Climate Change

Content of paper emphasizes the significant influence of soil health on global warming and climate stability. Soil affects the Earth's carbon cycle by acting as a source and sink of greenhouse gases. Climate is considered important a factor in soil formation, but also soils also have an impact on the climate. Therefore, soils are affected by the current climate change as well, particularly because they may release excessive amounts of carbon dioxide (CO2) and other greenhouse gases (GHG) as a result of changing their usage or poor management or human wrong practices. The pressure that climate change places on soil ecosystems has a significant impact on agriculture, biodiversity, and ecosystem services. For effective climate mitigation and adaptation policies to be developed, it is essential to understand these relationships. Worthwhile that the greatest soil management practices for reducing climate change focus on increasing soil organic matter content and water retention. The enormous carbon and nitrogen (N) store that is soil. acting as a possible regulator of the CO2, N2O, and CH4—the three main greenhouse gases in the atmosphere. Because biota is the organic matter carrier to the soil, both in living organisms and through their decomposing remains, mature soils rich in life are frequently CO2 sinks. But heterotrophic organisms that live in soil are also OM net consumers, and they release CO2 into the atmosphere through respiration. The interactions between plants, soil organisms, and abiotic soil conditions are actually changing as a result of climate change, which has an impact on plant performance, plant diversity, and community structure. The loss of soil organic matter (OM) and its development to the atmosphere quickly became a significant effect of tillage and any other activity, agricultural or otherwise, that disturbs the natural soils since then. It is anticipated that the areas affected by salinization would increase due to climate change which affects the suitability of the soil agriculture or any other development purposes.The conclusion of the current study Carbon sequestration can reduced the green house gas emission.