An assessment of the impacts of climate extremes on the vegetation in Mongolian Plateau: Using a scenarios-based analysis to support regional adaptation and mitigation options

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The Mongolian Plateau has a great impact on the ecological security in northern China. Vegetation has an important indicator effect on climate change and ecological environment. The spatial-temporal pattern and trend of vegetation are important indicators for evaluating regional ecological conditions. Based on MOD13Q1 NDVI data, we used R language to call Google Earth Engine service for monthly maximum synthesis in this study. And we then used R language terra package to complete the annual mean synthesis of the growing season, coefficient of variation calculation, Theil-Sen median trend analysis, Mann-Kendall test and Hurst index calculation, so as to form a dataset of 250m-resolution NDVI of spatio-temporal variations of vegetation in the growing season on the Mongolian Plateau (2001–2021). The dataset contains the spatial and temporal variation patterns and trend characteristics of vegetation on the Mongolian Plateau. Through data sharing, it can provide data support for scientific understanding of temporal and spatial variation of vegetation cover on the Mongolian Plateau.

PurposeThe paper aims to investigate the possible changes in mean temperature in the Mongolian Plateau associated with the 1.5 and 2°C global warming targets and how snow changes in the Mongolian Plateau when the mean global warming is well below 2°C or limited to 1.5°C.Design/methodology/approachIn total, 30 model simulations of consecutive temperature and precipitation days from Coupled Model Inter-comparison Project Phase 5 (CMIP5) are assessed in comparison with the 111 meteorological monitoring stations from 1961–2005. Multi-model ensemble and model relative error were used to evaluate the performance of CMIP5 models. Slope and the Mann–Kendall test were used to analyze the magnitude of the trends and evaluate the significance of trends of snow depth (SD) from 1981 to 2014 in the Mongolian Plateau.FindingsSome models perform well, even better than the majority (80%) of the models over the Mongolian Plateau, particularly HadGEM2-CC, CMCC-CM, BNU-ESM and GFDL-ESM2M, which simulate best in consecutive dry days (CDD), consecutive wet days (CWD), cold spell duration indicator (CSDI) and warm spell duration indicator (WSDI), respectively. Emphasis zones of WSDI on SD were deeply analysed in the 1.5 and 2 °C global warming period above pre-industrial conditions, because it alone has a significant negative relation with SD among the four indices. It is warmer than before in the Mongolian Plateau, particularly in the southern part of the Mongolian Plateau, indicating less SD.Originality/valueProviding climate extremes and SD data sets with different spatial-temporal scales over the Mongolian Plateau. Zoning SD potential risk areas and proposing adaptations to promote regional sustainable development.

Well-to-wheel greenhouse gas emissions of electric versus combustion vehicles from 2018 to 2030 in the US

The Earth's surface temperature is steadily increasing due to the accumulation of greenhouse gases, a phenomenon known as global warming. Human activities are the root cause of this significant global issue. Reducing greenhouse gas (GHG) emissions is one of the most critical actions in climate change mitigation. Organizations can engage in activities that promote change and reduce greenhouse gases by acknowledging the significance of addressing climate change. By reducing GHG emissions and promoting the use of renewable energy, organizations can begin to address environmental issues. Therefore, the purpose of this investigation is to assess the reduction of GHG emissions in an educational institution by substituting electricity consumption from the electrical grid with renewable energy in the form of a solar PV rooftop on-grid system. The School of Renewable Energy's GHG emissions were assessed, covering three scopes of GHG emissions activities: direct emissions, indirect emissions, and other indirect emissions. The organization's activity data were collected over a 12-month period. Without installing a solar panel system, the organization reported total GHG emissions of 310.40 tCO2e, relying solely on imported electricity for internal use. The highest GHG emissions were from Scope 2, amounting to 239.38 tCO2e, primarily due to electricity importation. Scope 3 had the second highest GHG emissions, totaling 65.76 tCO2e, resulting from employee commuting and the use of purchased goods such as paper and tap water. Scope 1 had the lowest GHG emissions at 5.26 tCO2e, produced by the combustion of diesel and gasoline in both stationary and mobile sources, as well as CH4 emissions from the septic tank. The percentage of GHG emissions from Scope 2 activities was 77.12%, which was considered to have a significant environmental impact and contribute to global warming. This was because 478,851 kWh of electricity were imported. The installation of on-grid solar cells for power generation reduced imported electricity to 113,120 kWh. Consequently, GHG emissions from Scope 2 decreased to 56.55 tCO2e, leading to an overall reduction in the organization's GHG emissions to 127.57 tCO2e. The organization's GHG emissions decreased by 182.83 tCO2e as a result of using alternative energy to generate electricity. This assessment can serve as a database for educational institutions and prepare the government to report greenhouse gas emissions. Furthermore, it can serve as carbon credits for trading and exchanging carbon with other organizations to offset GHG emissions from various activities. In addition, it endorses the government's goal of achieving carbon neutrality and net zero emissions in the future.

Dairy production systems represent a significant source of air pollutants such as greenhouse gases (GHG), that increase global warming, and ammonia (NH3), that leads to eutrophication and acidification of natural ecosystems. Greenhouse gases and ammonia are emitted both by conventional and organic dairy systems. Several studies have already been conducted to design practices that reduce greenhouse gas and ammonia emissions from dairy systems. However, those studies did not consider options specifically applied to organic farming, as well as the multiple trade-offs occurring between these air pollutants. This article reviews agricultural practices that mitigate greenhouse gas and ammonia emissions. Those practices can be applied to the most common organic dairy systems in northern Europe such as organic mixed crop-dairy systems. The following major points of mitigation options for animal production, crop production and grasslands are discussed. Animal production: the most promising options for reducing greenhouse gas emissions at the livestock management level involve either the improvement of animal production through dietary changes and genetic improvement or the reduction of the replacement rate. The control of the protein intake of animals is an effective means to reduce gaseous emissions of nitrogen, but it is difficult to implement in organic dairy farming systems. Considering the manure handling chain, mitigation options involve housing, storage and application. For housing, an increase in the amounts of straw used for bedding reduces NH3 emissions, while the limitation of CH4 emissions from deep litter is achieved by avoiding anaerobic conditions. During the storage of solid manure, composting could be an efficient mitigation option, depending on its management. Addition of straw to solid manure was shown to reduce CH4 and N2O emissions from the manure heaps. During the storage of liquid manure, emptying the slurry store before late spring is an efficient mitigation option to limit both CH4 and NH3 emissions. Addition of a wooden cover also reduces these emissions more efficiently than a natural surface crust alone, but may increase N2O emissions. Anaerobic digestion is the most promising way to reduce the overall greenhouse gas emissions from storage and land spreading, without increasing NH3 emissions. At the application stage, NH3 emissions may be reduced by spreading manure during the coolest part of the day, incorporating it quickly and in narrow bands. Crop production: the mitigation options for crop production focus on limiting CO2 and N2O emissions. The introduction of perennial crops or temporary leys of longer duration are promising options to limit CO2 emissions by storing carbon in plants or soils. Reduced tillage or no tillage as well as the incorporation of crop residues also favour carbon sequestration in soils, but these practices may enhance N2O emissions. Besides, the improvement of crop N-use efficiency through effective management of manure and slurry, by growing catch crops or by delaying the ploughing of leys, is of prime importance to reduce N2O emissions. Grassland: concerning grassland and grazing management, permanent conversion from arable to grassland provides high soil carbon sequestration while increasing or decreasing the livestock density seems not to be an appropriate mitigation option. From the study of the multiple interrelations between gases and between farm compartments, the following mitigation options are advised for organic mixed crop-dairy systems: (1) actions for increasing energy efficiency or fuel savings because they are beneficial in any case, (2) techniques improving efficiency of N management at field and farm levels because they affect not only N2O and NH3 emissions, but also nitrate leaching, and (3) biogas production through anaerobic digestion of manure because it is a promising efficient method to mitigate greenhouse gas emissions, even if the profitability of this expensive investment needs to be carefully studied. Finally, the way the farmer implements the mitigation options, i.e. his practices, will be a determining factor in the reduction of greenhouse gas and NH3 emissions.

Spatial heterogeneity of factors affecting GHG emission intensity in urban water supply and wastewater treatment systems in China

The influence of crop and chemical fertilizer combinations on greenhouse gas emissions: A partial life-cycle assessment of fertilizer production and use in China

Whole-farm systems modelling of greenhouse gas emissions from pastoral suckler beef cow production systems

To improve how extreme events and climate variations are managed, there is a need to foster a deeper understanding of their interconnections. Consistent with this objective, this paper describes how precipitation extremes change both temporally and spatially in the Inner Mongolian Plateau (IMP), China and explains their causal factors. The paper refers to data collected from 43 meteorological stations in IMP and describes how precipitation extremes formed and how they influence agriculture. Data gathered and presented in this paper may be useful in understanding the extent to which the IMP is being influenced by global environmental change. This study reveals that the eleven precipitation extremes indices, except the number of precipitation days with over 0.5 mm (R0.5), number of heavy precipitation days (R10), and total precipitation in wet days (PRCPTOT), decreased in the IMP between 1959 and 2014, and most of them were non-significant in temporal. But the dry index has a larger magnitude decreasing trend than that of the wet indices, which can indicate that the dry situation was alleviated in IMP during the study interval. This study also indicated that precipitation extremes have strong relationships with elevation, latitude, and longitude. Atmospheric circulation and topography may be further primary reasons which result in the spatial variation characteristics in precipitation extremes over the IMP. Decreases in precipitation extremes, together with human activities such as livestock improvement and ecological restoration programs, has a positive effect in gross output value of agriculture and animal husbandry in the IMP. The results contribute to a deeper insight on the possible impacts of precipitation extremes and support the development of appropriate adaptation and mitigation strategies to cope with climate extremes. This paper further proposes science-based policies for grassland protection, agriculture, and animal husbandry on the national or regional and herdsman scales.

Abstract. Although the concept of producing higher yields with reduced greenhouse gas (GHG) emissions is a goal that attracts increasing public and scientific attention, the trade-off between high yields and GHG emissions in intensive agricultural production is not well understood. Here, we hypothesize that there exists a mechanistic relationship between wheat grain yield and GHG emission, and that could be transformed into better agronomic management. A total 33 sites of on-farm experiments were investigated to evaluate the relationship between grain yield and GHG emissions using two systems (conventional practice, CP; high-yielding systems, HY) of intensive winter wheat (Triticum aestivum L.) in China. Furthermore, we discussed the potential to produce higher yields with lower GHG emissions based on a survey of 2938 farmers. Compared to the CP system, grain yield was 39% (2352 kg ha−1) higher in the HY system, while GHG emissions increased by only 10%, and GHG emission intensity was reduced by 21%. The current intensive winter wheat system with farmers' practice had a median yield and maximum GHG emission rate of 6050 kg ha−1 and 4783 kg CO2 eq ha−1, respectively; however, this system can be transformed to maintain yields while reducing GHG emissions by 26% (6077 kg ha−1, and 3555 kg CO2 eq ha−1). Further, the HY system was found to increase grain yield by 39% with a simultaneous reduction in GHG emissions by 18% (8429 kg ha−1, and 3905 kg CO2 eq ha−1, respectively). In the future, we suggest moving the trade-off relationships and calculations from grain yield and GHG emissions to new measures of productivity and environmental protection using innovative management technologies.

Bioenergy from perennial grasses mitigates climate change via displacing fossil fuels and storing atmospheric CO2 belowground as soil carbon. Here, we conduct a critical review to examine whether increasing plant diversity in bioenergy grassland systems can further increase their climate change mitigation potential. We find that compared with highly productive monocultures, diverse mixtures tend to produce as great or greater yields. In particular, there is strong evidence that legume addition improves yield, in some cases equivalent to mineral nitrogen fertilization at 33–150 kg per ha. Plant diversity can also promote soil carbon storage in the long term, reduce soil N2O emissions by 30%–40%, and suppress weed invasion, hence reducing herbicide use. These potential benefits of plant diversity translate to 50%–65% greater life-cycle greenhouse gas savings for biofuels from more diverse grassland biomass grown on degraded soils. In addition, there is growing evidence that plant diversity can accelerate land restoration. Bioenergy from perennial grasses mitigates climate change via displacing fossil fuels and storing atmospheric CO2 belowground as soil carbon. Here, we conduct a critical review to examine whether increasing plant diversity in bioenergy grassland systems can further increase their climate change mitigation potential. We find that compared with highly productive monocultures, diverse mixtures tend to produce as great or greater yields. In particular, there is strong evidence that legume addition improves yield, in some cases equivalent to mineral nitrogen fertilization at 33–150 kg per ha. Plant diversity can also promote soil carbon storage in the long term, reduce soil N2O emissions by 30%–40%, and suppress weed invasion, hence reducing herbicide use. These potential benefits of plant diversity translate to 50%–65% greater life-cycle greenhouse gas savings for biofuels from more diverse grassland biomass grown on degraded soils. In addition, there is growing evidence that plant diversity can accelerate land restoration.

Devising policies for a low carbon city requires a careful understanding of the characteristics of urban residential lifestyle and consumption. The production-based accounting approach based on top-down statistical data has a limited ability to reflect the total greenhouse gas (GHG) emissions from residential consumption. In this paper, we present a survey-based GHG emissions accounting methodology for urban residential consumption, and apply it in Xiamen City, a rapidly urbanizing coastal city in southeast China. Based on this, the main influencing factors determining residential GHG emissions at the household and community scale are identified, and the typical profiles of low, medium and high GHG emission households and communities are identified. Up to 70% of household GHG emissions are from regional and national activities that support household consumption including the supply of energy and building materials, while 17% are from urban level basic services and supplies such as sewage treatment and solid waste management, and only 13% are direct emissions from household consumption. Housing area and household size are the two main factors determining GHG emissions from residential consumption at the household scale, while average housing area and building height were the main factors at the community scale. Our results show a large disparity in GHG emissions profiles among different households, with high GHG emissions households emitting about five times more than low GHG emissions households. Emissions from high GHG emissions communities are about twice as high as from low GHG emissions communities. Our findings can contribute to better tailored and targeted policies aimed at reducing household GHG emissions, and developing low GHG emissions residential communities in China.

Dairy production systems represent a significant source of air pollutants such as greenhouse gases (GHG), that increase global warming, and ammonia (NH3), that leads to eutrophication and acidification of natural ecosystems. Greenhouse gases and ammonia are emitted both by conventional and organic dairy systems. Several studies have already been conducted to design practices that reduce greenhouse gas and ammonia emissions from dairy systems. However, those studies did not consider options specifically applied to organic farming, as well as the multiple trade-offs occurring between these air pollutants. This article reviews agricultural practices that mitigate greenhouse gas and ammonia emissions. Those practices can be applied to the most common organic dairy systems in northern Europe such as organic mixed crop-dairy systems. The following major points of mitigation options for animal production, crop production and grasslands are discussed. Animal production: the most promising options for reducing greenhouse gas emissions at the livestock management level involve either the improvement of animal production through dietary changes and genetic improvement or the reduction of the replacement rate. The control of the protein intake of animals is an effective means to reduce gaseous emissions of nitrogen, but it is difficult to implement in organic dairy farming systems. Considering the manure handling chain, mitigation options involve housing, storage and application. For housing, an increase in the amounts of straw used for bedding reduces NH3 emissions, while the limitation of CH4 emissions from deep litter is achieved by avoiding anaerobic conditions. During the storage of solid manure, composting could be an efficient mitigation option, depending on its management. Addition of straw to solid manure was shown to reduce CH4 and N2O emissions from the manure heaps. During the storage of liquid manure, emptying the slurry store before late spring is an efficient mitigation option to limit both CH4 and NH3 emissions. Addition of a wooden cover also reduces these emissions more efficiently than a natural surface crust alone, but may increase N2O emissions. Anaerobic digestion is the most promising way to reduce the overall greenhouse gas emissions from storage and land spreading, without increasing NH3 emissions. At the application stage, NH3 emissions may be reduced by spreading manure during the coolest part of the day, incorporating it quickly and in narrow bands. Crop production: the mitigation options for crop production focus on limiting CO2 and N2O emissions. The introduction of perennial crops or temporary leys of longer duration are promising options to limit CO2 emissions by storing carbon in plants or soils. Reduced tillage or no tillage as well as the incorporation of crop residues also favour carbon sequestration in soils, but these practices may enhance N2O emissions. Besides, the improvement of crop N-use efficiency through effective management of manure and slurry, by growing catch crops or by delaying the ploughing of leys, is of prime importance to reduce N2O emissions. Grassland: concerning grassland and grazing management, permanent conversion from arable to grassland provides high soil carbon sequestration while increasing or decreasing the livestock density seems not to be an appropriate mitigation option. From the study of the multiple interrelations between gases and between farm compartments, the following mitigation options are advised for organic mixed crop-dairy systems: (1) actions for increasing energy efficiency or fuel savings because they are beneficial in any case, (2) techniques improving efficiency of N management at field and farm levels because they affect not only N2O and NH3 emissions, but also nitrate leaching, and (3) biogas production through anaerobic digestion of manure because it is a promising efficient method to mitigate greenhouse gas emissions, even if the profitability of this expensive investment needs to be carefully studied. Finally, the way the farmer implements the mitigation options, i.e. his practices, will be a determining factor in the reduction of greenhouse gas and NH3 emissions.KeywordsAgricultureGreenhouse gasAmmoniaAbatementMixed crop-dairy systemsOrganicLivestockManureGrasslandCarbon storageSoil carbon sequestration

Taking the Mongolian Plateau as the study area, the MODIS normalized difference vegetation index (NDVI) and the land surface temperature (LST) in the growing season from 2000 to 2019 were used to construct the NDVI-LST feature space, and based on which the temperature vege-tation dryness index (TVDI) of the Mongolian Plateau was calculated. We used Theil-Sen Median trend analysis, Mann-Kendall test, and Hurst index method to analyze the spatial and temporal varia-tions and future trends of TVDI on the Mongolian Plateau. Furthermore, we examined the relationship between meteorological factors and TVDI on the Mongolian Plateau using partial correlation analysis. The results showed that the TVDI of the Mongolian Plateau during 2000-2019 showed an increasing trend with a rate of 0.0001·a-1, indicating that the Mongolian Plateau's drought condition became heavier slightly in the last 20 years. The drought condition in meadow steppe and typical steppe gradually decreased, and that in desert steppe and alpine grassland was increased. The average Hurst index of TVDI in the growing season was 0.45, and the area with TVDI less than 0.5 accounted for 71.5% of the total area, which indicated that the TVDI during 2000-2019 in most areas turned opposite to the past. In the future, the drought condition in the central desert steppe area and the eastern meadow steppe area might increase, and that in most of the typical steppe and the desert steppe in Inner Mongolia tended to decrease. The drought change in the alpine grassland area was uncertain. There was a significant positive correlation between the TVDI and temperature in 33.6% area of the Mongolian Plateau and a significant negative correlation between the TVDI and precipitation in 34.8% of the area. Moreover, the meteorological factors heavily affected the typical steppe.