Greenhouse Gas Emission Rates Research Articles

Analysis of the Influence of Training and Feedback Based on Event Data Recorder Information to Improve Safety, Operational and Economic Performance of Road Freight Transport in Brazil

Road transport is the principal means of transporting freight and passengers in most developing countries, but several factors, both alone and in conjunction, contribute to increased inefficiency, risk and instability in the sector. The main factors are related to the high number of accidents, structural precariousness, fleet obsolescence, low-skilled drivers and high rates of greenhouse gas emissions. This paper evaluates the influence of implementing a training and feedback procedure associated with event data recorder (EDR) systems for the promotion of better behavior among professional drivers based on safety, operation and economy criteria. The analyses are based on interventions that were carried out during four monitoring phases using data generated by vehicles collected over 13 months of research. The data were converted into indicators and evaluated individually against the criteria and through data envelopment analysis (DEA). The analyses led to the conclusions that the use of EDR systems had positive impacts on all three of the criteria under analysis, and that safety levels can be increased without having to reduce productivity or increase fuel consumption. However, the safety criterion was more sensitive to the association between the technology and training process applied, leading to significant reductions in the indicators analyzed. The study contributes to the association between the methods of analysis and the adoption of specific indicators derived from time variables, leading to the conclusion that the use of EDR systems associated with management training and monitoring procedures can improve economic and operational results in road freight transport (RFT). Furthermore, using the trip data as a structural basis for the training and feedback proved to be very promising for the reduction of unsafe behavior to avoid road accidents.

Implications of CMIP6 Projected Drying Trends for 21st Century Amazonian Drought Risk

AbstractRecent exceptionally hot droughts in Amazonia have highlighted the potential role of global warming in driving changes in rainfall and temperatures in the region. The previous generation of global climate models projected that eastern Amazonia would receive less future precipitation while western Amazonia would receive more precipitation, but many of these models disagreed on future precipitation trends in the region. Here Coupled Modeling Intercomparison Project, Phase 6 (CMIP6) models are used to examine the shifting risk of eastern Amazonian droughts under high and low future greenhouse gas emissions scenarios. This new generation of models shows better agreement that most of the Amazonian basin will receive less future rainfall, with particularly strong agreement that eastern and southern Amazonia will dry in the 21st century. These models suggest that global warming may be increasing the likelihood of exceptionally hot drought in the region. With unabated global warming, recent particularly warm and severe droughts will become more common by midcentury, but reducing the rate of greenhouse gas emissions can make extremely hot and dry years less common in the future. Simulated future rainfall changes in Amazonia under high greenhouse gas emissions are associated with changes in the tropical Pacific, but many climate models struggle to reproduce observed trends in the tropical Pacific. These shortcomings highlight the need to improve confidence in global climate models' ability to simulate observed trends in the tropics, even if more CMIP6 models agree on the sign of future rainfall trends.

Analysis of regulative variables on greenhouse gas emissions and spatial pore gas concentrations with modeling during large-scale trough composting

Regulative composting variables, like aeration, turning and additive, are critical factors for low-emission and eco-friendly aerobic composting. The main variables (aeration, turning, and additive) on greenhouse gas (GHG) emission rates and spatial GHG concentrations in the pores of composting piles during the large-scale composting were investigated under a typical trough composting system. An engineering model combined momentum transfer was built to simulate the airflow, temperature, and oxygen concentration distribution; thus, the composting equipment parameters could be preliminarily ensured. The aeration period emitted more carbon dioxide per unit time than the non-aeration period. Over 83% of methane was emitted during nonaeration period. GHG emissions in after-turning period were lower than those both in the nonaeration and aeration periods. Through modeling, momentum lost around 34% by frictional resistance when air flows in pipes. The difference of inlet oxygen velocity distribution of pipe’s pores was not over 10%, because high pressure provided by a fan could slow down the frictional resistance along the pipeline. The temperature distribution simulation followed the rules of heat diffusion and convection. The oxygen concentration in piles was transferred by its concentration condition fitting Fick law. Model well simulated the actual condition and composting routine could provide support for composting system design and composting management. Because of the complex condition of large-scale composting, modeling of the airflow simulation on GHG emissions should be further investigated.

Assessing the mitigation of greenhouse gas emissions from a green infrastructure-based urban drainage system

Green infrastructure (GI) is a low-carbon solution for urban rainwater management. Hydrological processes and the corresponding emissions of greenhouse gas (GHG) during rainfall events are optimized by GI when the latter is compared with a traditional urban drainage system. This study establishes an city-scale quantitative analysis, based on hydrological processes, with which to assess the contribution of GIs to low-carbon urban drainage systems and cities. The emission factor method is applied to measure GHG emissions. Attributable sources of emissions are wastewater treatment plants and wastewater and rainwater pumps. The amount and rate of change in GHG emissions were selected as indicators of the impacts of GI-based urban drainage systems and a case study was conducted in Dongying, China, based on 48 hydrological scenarios from 1970 to 2017. The amount of annual GHG emissions decreased by 3752.5 to 26238.9 tons of CO2 equivalent at an average of 10677.3 tons/a. The rate of annual GHG emissions decreased by 25.9–68.7% with an average reduction of 45.9%. An S-shaped logistic curve fit the data, indicated that annual rainfall is non-linearly and positively correlated with both the amount and rate of annual GHG emissions mitigated. The probability of benefits to GHG emissions in the 48 hydrological scenarios is analyzed based on a Pearson type III distribution curve. These findings can provide information that local authorities can use to guide policies towards their goals of applying GIs to mitigate GHG emissions in the urban drainage system.

EU land use futures: modelling food, bioenergy and carbon dynamics

This paper presents an original system dynamics model, which aims to assess how changes in diet, agricultural practices, bioenergy and forestry could help reduce greenhouse gas emissions. We demonstrate that changes in types and quantities of food consumed and reductions in food wastes along with sustainable bioenergy and forestry dynamics would materially assist the EU in meeting its 2050 climate mitigation obligations. We find that overall rates of EU-28 greenhouse gas emissions are highly sensitive to the food trade balance, both within and outside the EU. Land use itself is often under-represented as a major option for carbon mitigation in policy strategies, but our results show that it must become a central component aligned with energy system decarbonization if material levels of warming mitigation are to be achieved.

Potential of Alternate Wetting and Drying Irrigation Practices for the Mitigation of GHG Emissions from Rice Fields: Two Cases in Central Luzon (Philippines)

Reducing methane (CH4) emission from paddy rice production is an important target for many Asian countries in order to comply with their climate policy commitments. National greenhouse gas (GHG) inventory approaches like the Tier-2 approach of the Intergovernmental Panel on Climate Change (IPCC) are useful to assess country-scale emissions from the agricultural sector. In paddy rice, alternate wetting and drying (AWD) is a promising and well-studied water management technique which, as shown in experimental studies, can effectively reduce CH4 emissions. However, so far little is known about GHG emission rates under AWD when the technique is fully controlled by farmers. This study assesses CH4 and nitrous oxide (N2O) fluxes under continuous flooded (CF) and AWD treatments for seven subsequent seasons on farmers’ fields in a pumped irrigation system in Central Luzon, Philippines. Under AWD management, CH4 emissions were substantially reduced (73% in dry season (DS), 21% in wet season (WS)). In all treatments, CH4 is the major contributor to the total GHG emission and is, thus, identified as the driving force to the global warming potential (GWP). The contribution of N2O emissions to the GWP was higher in CF than in AWD, however, these only offset 15% of the decrease in CH4 emission and, therefore, did not jeopardize the strong reduction in the GWP. The study proves the feasibility of AWD under farmers’ management as well as the intended mitigation effect. Resulting from this study, it is recommended to incentivize dissemination strategies in order to improve the effectiveness of mitigation initiatives. A comparison of single CH4 emissions to calculated emissions with the IPCC Tier-2 inventory approach identified that, although averaged values showed a sufficient degree of accuracy, fluctuations for single measurement points have high variation which limit the use of the method for field-level assessments.

Depth dependence of temperature sensitivity of soil carbon dioxide, nitrous oxide and methane emissions

Carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) are three important greenhouse gases (GHGs) associated with rising temperature. Their temperature sensitivities (Q10) play important roles in predicting soil–atmosphere gas exchange under global warming. Few studies have simultaneously evaluated the variation in Q10 of CO2, N2O and CH4 emissions across different soil depths. Here, we sampled soils from 13 sites along a climatic transect in temperate grasslands of northern China, including meadow steppe, typical steppe and desert steppe. Soil samples were collected from five depths (0–10, 10–20, 20–40, 40–60 and 60–100 cm) and incubated at four temperatures (5, 15, 25 and 35 °C). We determined GHG emission rates, corresponding biotic (microbial biomass, microbial abundance and composition, and extracellular enzyme activities) and abiotic (soil carbon, nitrogen content, and soil pH) factors. The average Q10 of CO2 and N2O emissions differed non-significantly among steppe types, while the effect of steppe type on Q10 of CH4 emission was strongly affected by measured temperature ranges. Q10 of CO2 and N2O emissions declined with soil depth, but showed no significant differences for CH4. The mechanisms driving the variations in Q10 of GHG emissions among soil depths changed with steppe types. Q10 of CO2 emission was significantly correlated with substrate quality and microbial biomass in meadow steppe and desert steppe, and with microbial abundance and composition in typical steppe. Q10 of N2O emission was significantly influenced by microbial biomass in meadow steppe, soil pH in typical steppe, and substrate quality and microbial biomass in desert steppe, respectively. Q10 of CH4 emission was significantly associated with microbial biomass in typical steppe, and with substrate quality in meadow steppe and desert steppe, respectively. Our findings emphasized the importance of considering steppe type when assessing vertical dynamics of Q10 of GHG emissions.

Forage legumes in grass pastures in tropical Brazil and likely impacts on greenhouse gas emissions: A review

AbstractBeef cattle producers seldom use fertilizers for their pastures in tropical regions of Brazil. Slowly, this is changing but because of the need for repeated applications, N fertilizer is rarely applied. The introduction of a forage legume is an appropriate solution for this problem, but until recently adoption has been very low as the legumes generally have not persisted in the sward. We report research on how grazing management can affect the persistence of stoloniferous legumes in pastures of Brachiaria spp. and the problems of establishing and maintaining crown‐forming legumes such as Stylosanthes spp. With suitable management, milk or bovine carcass yields can be equal or greater from mixed than from grass‐alone pastures fertilized with 120 or 150 kg Nha‐1 year−1. In addition to savings in CO2 emissions from fossil fuels for the production and distribution of N fertilizers, nitrous oxide emissions from cattle excreta and legume residues are lower than those from N‐fertilized brachiaria grass monocultures. Other studies indicate that enteric methane emissions from cattle may be mitigated when forage legumes are included in their diet. The use of forage legumes in mixed pastures for tropical regions is emerging as a feasible strategy to keep meat and milk production at acceptable levels with reduced greenhouse gas emission rates.

Optimizing bike sharing systems from the life cycle greenhouse gas emissions perspective

Bike sharing systems (BSSs), being viewed as providing green transportation modes, are growing rapidly in recent years. While BSS operators try to improve the system performance through bike rebalancing and launching more bikes, the current BSSs are facing several sustainability challenges. Bike oversupply could bring intensive greenhouse gas (GHG) emissions due to manufacturing excessive bikes, while frequent bike rebalancing could significantly increase fuel consumption of rebalancing vehicles. Existing studies only optimized given BSS from the system operational perspective (i.e. rebalancing), with predetermined bike fleet size and rebalancing frequencies. However, the bike fleet size and rebalancing should also be optimized from the life cycle’s perspective. This study proposes a framework to obtain the optimal bike fleet size and rebalancing strategy to minimize the system’s life cycle GHG emissions, integrating a simulation model for fleet size estimation, an optimization model for bike rebalancing, and a life cycle assessment (LCA) model to quantify the system’s GHG emission rate. The framework is applied to a dock-less BSS in Xiamen, China as a case study to evaluate the tradeoff between having more bikes (requiring less rebalancing) and more frequent rebalancing (requiring fewer bikes). Our results show that (1) the current BSS in Xiamen is significantly oversupplied, with only 15% of current bikes needed to serve the same demands; (2) decreasing bike fleet size through more frequent rebalancing will increase the system’s life cycle GHG emissions; and (3) choosing appropriate rebalancing fleet size, loading capacity, and setting multiple depots can reduce a BSS’ rebalancing GHG emissions.

Evaluation of energy and environmental performances of Solar Photovoltaic-based Targeted Poverty Alleviation Plants in China

The projects that combine solar photovoltaics (PV) and poverty alleviation (PA) are the explorations of sustainable development (SD) from the Chinese government, aiming at both reducing the number of rural poor and the intensity of carbon emissions. Currently, the actual energy and environmental performances of those Photovoltaic-based Targeted Poverty Alleviation Plants (PV-PAPs) remain to be validated. Based on the field survey data from 23 grid-connected PV-PAPs in 7 provinces of China, with a total installed capacity of 51.39 MW, this study evaluated their energy and environmental benefits by adopting the Life Cycle Assessment (LCA) and the Net Energy Analysis (NEA) methods. The following indicators of PV-PAPs were calculated: Energy Payback Time (EPBT), Energy Return on Investment (EROIPE-eq), Greenhouse Gas Emission Rate (GHGe-R) and Carbon Payback Time (CPBT). The results show that: (1) The EPBT of 23 power stations would be 0.79–1.94 years, the EROIPE-eq range from 15.48 to 38.15, the range of GHGe-R would be 43.34–106.78 g/kWh, and the CPBT range from 1.88 to 5.11 years. Even in areas with poor solar radiation, PV-PAPs still have good energy efficiency and environmental benefits. (2) The indirect environmental cost incurred by human factors should be highlighted. It might lead to the change of benefits, such as the GHGe-R, which might fluctuate from 0 to 51.44 g/kWh for the power plants with similar technical specifications. (3) Compared with traditional coal-fired electricity generation (EG), the PV EG could reduce carbon emissions by 87.35–94.9%. This study reveals the status and effects of PV-PAPs in China, and provides practical evidence for further large-scale practice of solar PV in China, which could also provide a basis for decision-making of policy makers. Finally, policy recommendations were proposed to help promote the SD of the PV industry in China.

Observación espacial y análisis de la relación entre las emisiones atmosféricas de CO2 y el tamaño de las ciudades en Chile

Las tasas de crecimiento urbano han tenido un desarrollo explosivo impactando fuertemente el sistema de soporte vital de nuestro planeta, por lo que medir y comprender la relación entre el crecimiento urbano y las tasas de emisiones de gases de efecto invernadero resulta esencial para asegurar la sustentabilidad de los ambientes donde vivirá el 67% de la población mundial en el año 2050. Este artículo busca, por un lado, establecer la posibilidad de evaluar emisiones a partir de fuentes independientes a la fuente emisora y por otro, describir la relación entre emisiones de CO2 y el tamaño del sistema de ciudades de Chile. Para ello, se caracterizaron las emisiones de CO2 y sus anomalías para Chile continental utilizando sensores remotos (OCO-2). Se evaluó además la relación bivariada entre emisiones de CO2 declaradas en los inventarios locales del RETC e indicadores de desarrollo urbano de 20 ciudades chilenas. Si bien es posible estimar las emisiones de CO2 a partir de sensores remotos a escala regional, la baja de resolución y cobertura espacial de datos válidos capturados por el satélite limita la asociación de emisiones al ambiente urbano en Chile. Sin embargo, los datos declarados en RETC muestran que las emisiones a nivel de ciudad presentan una relación sublineal para las tres variables consideradas: Población (β=0,89; r2=0,73), Área urbana (β=0,99; r2=0,74) y PIB (β=0,68; r2=0,55). Estos resultados coinciden con descripciones en la literatura, y sugieren que las emisiones de CO2 en ciudades de tamaño creciente está asociada a economías de escala en la que los habitantes de una ciudad comparten los costos de emisión, producto de una mayor eficiencia en el uso de la infraestructura y los servicios a medida que la ciudad crece en población, área y producción. Lo que se traduce finalmente en menores tasas de emisión per cápita.

Pulsed Current Based Fast Charging Methods for Li-Ion Battery

The increasing rate of greenhouse gas emissions from conventional cars and its impact on global warming in the recent years has led to the technological advancements in the evolution of electric vehicles. Developing fast charging methods for Li-ion batteries is one such technological advancement and soon it will be imperative to promote the usage of electric vehicles in increased numbers. However, fast charging of Li-ion battery accelerates aging mechanisms [1] and triggers thermal runaway condition. As a result, this study investigates pulsed current based fast charging methods employed on C/NMC batteries. Pulses of current at low frequency (mHz) [2] and high frequency (KHz) are used with an extended pulse current period, thanks to higher voltage limit based on ohmic drop compensation [3]. The findings of the experimental investigation clearly establishes that a compromise has to be found between relaxation period and temperature in order to achieve fast charging. For instance, on one hand, a 2C current pulse with an on duration of 3s and relaxation duration of 1s allows to save 45% of recharging time when compared with standard constant current-constant voltage charging (CC-CV) at 0.5C as shown in the figure below. On the other hand, the temperature variation does not exceed 20°C beyond ambient which is lower than that of its counterpart CC-CV at 2C. Hence, the experimental investigation successfully opens the doors to implement fast charging methods on C/NMC batteries by limiting the temperature rise, there by arresting the ageing of batteries and thermal runaway condition.Keyword: Li-ion, Fast charging, Current pulse, Ohmic drop compensation, Temperature, Thermal runaway. Figure 1

Cities and Greenhouse Gas Emissions: Moving Forward

Cities are blamed for the majority of greenhouse gas (GHG) emissions. So too are more affluent, highly urbanised countries. If all production- and consumption-based emissions that result from lifestyle and purchasing habits are included, urban residents and their associated affluence likely account for more than 80 per cent of the world’s GHG emissions. Attribution of GHG emissions should be refined. Apportioning responsibility can be misguided, as recent literature demonstrates that residents of denser city centres can emit half the GHG emissions of their suburban neighbours. It also fails to capture the enormous disparities within and across cities as emissions are lowest for poor cities and particularly low for the urban poor. This article presents a detailed analysis of per capita GHG emissions for several large cities and a review of per capita emissions for 100 cities for which peer-reviewed studies are available. This highlights how average per capita GHG emissions for cities vary from more than 15 tonnes of carbon dioxide equivalent (tCO2e) (Sydney, Calgary, Stuttgart and several major US cities) to less than half a tonne (various cities in Nepal, India and Bangladesh). The article discusses where GHG emissions arise and where mitigation efforts may be most effective. It illustrates the need to obtain comparable estimates at city level and the importance of defining the scope of the analysis. Emissions for Toronto are presented at a neighbourhood level, city core level and metropolitan area level, and these are compared with provincial and national per capita totals. This shows that GHG emissions can vary noticeably for the same resident of a city or country, depending on whether these are production- or consumption-based values. The methodologies and results presented form important inputs for policy development across urban sectors. The article highlights the benefits and drawbacks of apportioning GHG emissions (and solid waste generation) per person. A strong correlation between high rates of GHG emissions and solid waste generation is presented. Policies that address both in concert may be more effective as they are both largely by-products of lifestyles.

The effect of digestate and mineral fertilisation of cocksfoot grass on greenhouse gas emissions in a cocksfoot-based biogas production system

BackgroundClimate mitigation is a major consideration when choosing bioenergy systems. Anaerobic digestion of biomass is a bioenergy system, which is normally used for the treatment of manure or other residues, but cultivated energy crops may also provide a potential feedstock. One of the main crops for biogas production is still maize, but it may be desirable to replace it by perennial grasses, which also have high yields, but do not require as much management. The aim of this study was to analyse greenhouse gas (GHG) emissions in a biogas production system based on a perennial grass, cocksfoot, grown under different fertiliser application systems.MethodsField and laboratory experiments were carried out over a 7-year period to evaluate the influence of mineral nitrogen and digestate fertiliser application on cocksfoot biomass and biogas productivity. The obtained data were used to calculate GHG emissions and emission savings for the whole biogas production cycle, by use of the SimaPro v.8 software with the IMPACT 2002+ model, based on the climate change environmental impact category.ResultsProductivity of cocksfoot (Dactylis glomerata L.) was influenced by the annual rate of nitrogen applied as fertiliser, the fertiliser type and year, as influenced by the weather conditions. The biomass yield of cocksfoot fertilised with 180 kg nitrogen ha−1 year−1 was similar regardless if the nitrogen was applied as digestate or mineral fertiliser. At higher rates of nitrogen application (360–450 kg ha−1 year−1), higher yields and lower net GHG emissions could be obtained from the biogas production cycle when the nitrogen was applied as digestate compared to mineral fertiliser, especially in dry years. Energy input over the whole cycle was mainly influenced by the type of fertiliser and the biomass yield. Mineral fertiliser generally caused higher levels of GHG emissions than organic digestate fertiliser, when the same amount of energy is produced.ConclusionsThe cocksfoot grass-based biogas production system showed that a significant GHG emission saving potential exists, if nitrogen is added as digestate instead of mineral fertiliser, for similar yields of biomass and energy from biogas. Cocksfoot grass fertilised with digestate is thus a promising feedstock for biogas production.

An empirical case study on Indian consumers' sentiment towards electric vehicles: A big data analytics approach

Today, climate change due to global warming is a significant concern to all of us. India's rate of greenhouse gas emissions is increasing day by day, placing India in the top ten emitters in the world. Air pollution is one of the significant contributors to the greenhouse effect. Transportation contributes about 10% of the air pollution in India. The Indian government is taking steps to reduce air pollution by encouraging the use of electric vehicles. But, success depends on consumer's sentiment, perception and understanding towards Electric Vehicles (EV). This case study tried to capture the feeling, attitude, and emotions of Indian consumers' towards electric vehicles. The main objective of this study was to extract opinions valuable to prospective buyers (to know what is best for them), marketers (for determining what features should be advertised) and manufacturers (for deciding what features should be improved) using Deep Learning techniques (e.g Doc2Vec Algorithm, Recurrent Neural Network (RNN), Convolutional Neural Network (CNN)). Due to the very nature of social media data, big data platform was chosen to analyze the sentiment towards EV. Deep Learning based techniques were preferred over traditional machine learning algorithms (Support Vector Machine, Logistic regression and Decision tree, etc.) due to its superior text mining capabilities. Two years data (2016 to 2018) were collected from different social media platform for this case study. The results showed the efficiency of deep learning algorithms and found CNN yield better results in-compare to others. The proposed optimal model will help consumers, designers and manufacturers in their decision-making capabilities to choose, design and manufacture EV.

Evolution of Green Industrial Growth between Europe and China based on the Energy Consumption Model

Greenhouse gas (GHG) emissions are an important factor in the evaluation of green industrial growth, when low GHG emissions along with high industrial growth are expected. In this paper, the improvement of sustainable development of industry in China (2007–2015) was investigated via analysis of the relationships between the GHG emissions and energy consumption in comparison to European countries. A hierarchical cluster analysis (HCA) was conducted to distinguish industrial growth with GHG emission and energy consumption structures. The results of this research indicated that green industrial growth in Europe had a negative annual rate of GHG emissions. This contributed to the ratio of renewable energy consumption increasing to a maximum of 33% and an average of 16%. In comparison, the GHG emissions in China increased at a rate of 50% to 77% in the main industrial provinces since 2007 with their rapid industrial growth. The rate of GHG emissions decreased after 2012, which was 7% or less than the rate of emissions in the industrial provinces. Contrary to in Europe, the decreasing rate of GHG emissions in China was attributed to the improvement of fossil energy efficiency, as renewable energy consumption was less than 10% in most industrial provinces. Our data analysis identified that the two different energy consumption strategies improved green industrial growth in Europe and China, respectively. Our data analysis identified the two different energy consumption strategies employed by Europe and China, each of which promoted green industrial growth in the corresponding areas. We concluded that China achieved green industrial growth through an increase in energy efficiency through technology updates to decrease GHG emissions, which we call the “China Model.” The “Europe Model” proved to be quite different, having the core characteristic of increasing renewable energy use.

ВЛИЯНИЕ «ЗЕЛЕНОЙ ЭКОНОМИКИ» НА ЭКОНОМИЧЕСКОЕ РАЗВИТИЕ И ЭКОЛОГИЧЕСКУЮ БЕЗОПАСНОСТЬ КАЗАХСТАНА


 
 
 Kazakhstan has a huge potential for the use of renewable energy sources, while being the state with the highest rates of greenhouse gas emissions in Central Asia. Despite significant economic, social and environmental benefits, the share of renewable energy in Kazakhstan's electricity production remains low, at 1.1% in 2017. The government intends to increase this figure to 50% by 2050. While Kazakhstan is experiencing some difficulties in diversifying its economy and energy resources, the inclusive concept of green growth is particularly important for the country.The adopted Strategy Kazakhstan 2050: A New Political Course of the Established State «Strategy - 2050» sets clear guidelines for building a sustainable and efficient economic model based on the country’s transition to a green development path.The article analyzes the current status of the transition to «green economy» including the development of renewable energy, green building, environmentally friendly transport, waste management, sustainable and efficient organic agriculture, and rational use of water resources. The scientific article focuses on the key risks, problems and obstacles to the development of the «green economy» in Kazakhstan, as well as offers recommendations and measures to solve existing problems. In addition, the article examines the methods of the government's transition to a «green economy», within which the planned tasks of a large-scale transition to a «green economy» are to be fulfilled.The article can be useful for those who are interested in sustainable economic growth: the government, energy companies, investors in the field of renewable energy and society as a whole.
 
 

Customized Medicine for Corals

[Extract] Coral reefs are facing unprecedented pressures, on a global scale. Alarming declines in coral abundance and diversity are occurring across the majority of reef systems, driven by the cumulative impacts of local stressors and rapidly changing climate (Hughes et al., 2017, 2018). Increases in the greenhouse gas emission (GGE) rates are linked with marine heatwaves which cause mass coral bleaching events, a phenomenon reported as the main threat to coral reefs into the future (Sweet and Brown, 2016). The recent global coral bleaching event from 2014 to 2017 resulted in extensive mortality impacting reef functioning in ways not previously recorded (Eakin et al., 2019). The knock-on effects of this global environmental extreme are still playing out with recent assessment on the Great Barrier Reef (GBR) demonstrating drastic declines in coral recruitment, which may fundamentally change the ecosystem dynamics across this region into the future (Hughes et al., 2019). In addition, regional stressors such as overfishing, poor water quality, and pollution can also severely affect the health state of corals and reefs (Shaver et al., 2018). Most agree that the reduction of GGE rates is the priority to ensure the persistence of coral reef ecosystems, however under current GGE projections, annual mass coral bleaching events are expected to occur as early as 2050 (National Academies of Science, Engineering and National Academies of Sciences, 2018). Even if GGE emissions are significantly reduced, further decline of reef health appears unavoidable due to the current accumulation of greenhouse gases in the atmosphere and the predicted lag period before any change will be observed (Hoegh-Guldberg et al., 2007; National Academies of Sciences, 2018). This poses a major problem to those caring for and managing reef ecosystems.

Economic and environmental assessment of reusing electric vehicle lithium-ion batteries for load leveling in the residential, industrial and photovoltaic power plants sectors

Reaching 70–80% of primary capacity, lithium-ion batteries must be replaced in electric vehicles. However, they could be reused in other applications such as energy storage stations. In this paper, an economic evaluation of reusage of lithium-ion packs for load leveling in the residential, industrial and photovoltaic power plants sectors have been investigated from subscriber and government aspects. Several repurposed electric vehicle battery packs have been taking into account for different tariffs and scenarios. It is found that utilization of battery can reduce electricity bill for residential consumers by 14.25% based on the current electricity market and 39.75% if the fine of the peak time consumption is tripled. However, the current subsidy rate in the electricity tariffs is the main barrier in terms of the payback period for homeowners. Moreover, it is found that decrease in the battery prices by 2035 as the only factor will not justify usage of repurposed battery in residential sector, furthermore, tariffs must also be regulated. Sensitivity analysis declared that a 20% reduction in the price of battery in residential sector, affects the internal rate of return by 164%. Meanwhile, increasing in the on-peak tariff can fluctuate it by 44%. Reusing electric vehicle batteries could be more profitable in the industrial sector due to the realistic tariff. In addition to the operation cost, government saving is analyzed from the initial cost aspect. Results illustrated that utilization of repurposed battery packs can reduce construction costs of new on-peak thermal power plants by 72.5% and 82% in the residential and industrial sectors, respectively. Finally, the effect of using repurposed lithium-ion battery packs on the emission rates of greenhouse gases and other air pollutants are surveyed. The reused batteries can be employed to achieve sustainable development.

Performance And Emission Evaluation Of A Biodiesel (Rice Bran Oil Methyl Ester) Fuelled Transportation Diesel Engine With And Without EGR

This research is aimed at finding a sustainable alternate source of energy that can be used as a substitute for conventional fuel sources, which are fast dwindling towards the point of exhaustion. Bio-diesels are viewed as an effective alternate source of energy which can be better than conventional fossil fuels in its performance, combustion and greenhouse gas emission rates. The oil of rice bran methyl ester is used for experimentation. The oil is blended in different ratios with pure diesel in a process known as blending. The various blends are then subjected to performance test in a diesel engine. The biodiesel blends have also been tested for emission properties with and without exhaust gas recirculation. The results reveal that rice bran biodiesel emits less amount of carbon monoxide emissions.