High Emission Levels Research Articles

Recycling of Disposable Surgical Instruments - Is It Worth It?

The German healthcare sector is responsible for 5.2% of the country's greenhouse gas emissions. One contributing factor is the enormous amount of waste generated daily in German hospitals, making them the fifth largest waste producer in Germany. Despite the potential for recycling, a significant portion of hospital waste is incinerated, as mandated by current regulations. This results in high levels of noxious CO2 emissions and the loss of valuable resources. The goal of this project was to demonstrate the feasibility of recycling complex, contaminated disposable surgical instruments.The study included frequently used disposable surgical instruments that could potentially be recycled as electronic waste. The instruments were wipe-disinfected and sterilised internally within the hospital. After sterilisation, the devices could be classified as electronic waste in consultation with the environmental authorities and then machine-recycled externally by a waste disposal company. Sorting machines shredded and separated the instruments into individual fractions of cables, plastics, different metals, and circuit boards, which were further processed into secondary raw materials.In the first six months (09/2022-03/2023), 239kg of material were recycled instead of being incinerated. This resulted in a reduction of 545kg CO2e. The metal content was estimated as 50% of the total weight; 30% were recyclable plastics, resulting in an 80% recycling rate. The ongoing recycling costs were 1.90€/kg after deducting revenues. Thus, recycling in this model was approximately 3.9 times as expensive as incineration. A survey of the operating theatre personnel found high satisfaction with the recycling project and a minimal additional workload of less than five minutes.We demonstrated that recycling of contaminated disposable surgical instruments is possible in coordination with government authorities. This approach avoids waste incineration and leads to a reduction in CO2-equivalent emissions. However, the higher costs of recycling and the requirement for in-house decontamination pose limitations on the implementation of such projects. To address this, it is necessary for lawmakers to reconsider current regulations and involve manufacturers in recycling costs to fully exploit the enormous recycling potential.

An Analysis of Emission Exhaust Gas on 4-Stroke Engine Based on IOT Gas Analyzer

According to the Air Quality Live Index (AQLI), Indonesia's air quality has continued to deteriorate in the last two decades, so Indonesia is officially ranked 17th as the country with the worst air quality in the world. This is due to the population explosion in Indonesia causing industrial activity to also increase. The high levels of exhaust emissions in vehicles, of course, requires the need for technology to measure vehicle exhaust gases to reduce the impact of air pollution. However, the procurement of exhaust emission test equipment is still expensive, so only certain class workshops have this tool. In addition, the reading results of the vehicle's OBD (On Board Diagnostic) system are only able to display the condition or reading value of the Lambda sensor because other gas sensors readings such as CO2, HC, and CO cannot be displayed on the OBD reading results. The purpose of this study is to describe the design of the tool and the results of measuring CO and HC levels through the Blynk application. Research methods that use several gas sensors, such as MQ-7 and TGS-2602 (CO gas) and MQ-2 and TGS-2611 (HC gas), are then compared with the measurement results of a standard gas analyzer. The results showed that the MQ-7 value is close to the accuracy at 1000 rpm and 5000 rpm, namely 99.68% and 99.49%, while the level of accuracy at 3000 rpm is 99.37%. The TGS-2602 sensor at 1000 rpm only has the best accuracy and accuracy, namely 99.67% and 99.77%. The level of accuracy of the MQ-2 sensor has the best value at 1000 rpm rotation, which is 95.71% and the level of accuracy has the highest value at 7000 rpm rotation, which is 100%. For the level of accuracy of the TGS-2611 sensor, it has an accuracy level of 1000 rpm rotation of 94.65% and the level of accuracy of the sensor obtains very good values ​​at 1000 rpm, 7000 rpm, and 9000 rpm rotation of 100%.

Analyzing Sustainable Practices in Fashion Supply Chain

Fast fashion brands create high quantities of synthetic, petroleum-based garments that result in high levels of textile waste and emissions. To change the dreadful tag of hazardous production, top-notch fast fashion leaders started paying attention towards adopting sustainable practices, including sustainable supply chain management (SSCM).This paper conducts a structured review of the annual reports on the topic of energy efficiency and environmental sustainability practices adopted by fashion brands in the supply chain management context. This study tries to identify the factors and classification influencing energy efficiency and environmental sustainability initiatives that impact supply chain performance, the customer perspective and the different technologies supporting energy efficiency and sustainable practices based on the analysis of the data related to the sustainability of top fashion brands from their past five year annual reports.

Determinants of Low-Carbon Logistics Capability Based on Dynamic fsQCA: Evidence from China’s Provincial Panel Data

The fast-paced growth of the logistics industry has contributed significantly to China’s high-quality economic development. However, the growth of the logistics industry is frequently accompanied by high levels of pollution, carbon emissions, and energy consumption. How to increase low-carbon logistics capacity has emerged as a research hotspot under the dual carbon goals. This study used entropy weight TOPSIS to evaluate the low-carbon logistics capacity and dynamic fuzzy-set qualitative comparative analysis (fsQCA) to shed light on the antecedent conditions that influenced low-carbon logistics capability by using panel data from 30 Chinese provinces between 2008 and 2021. Based on the empirical results, several conclusions are drawn: (1) The comprehensive score show that while province low-carbon logistics capacity varies, most of them exhibit a general growing tendency in most provinces, where Beijing, Shanghai, Tianjin, Guangdong and Zhejiang rank among the top five. (2) Three configurations, digital empower capital intensive type, digital empower labor intensive type, and green ecology plus technology innovation type that lead to better low-carbon logistics capacity. Related policy recommendations are proposed, including strengthening the synergistic development of the digital economy and the logistics industry, promoting research and development of green and innovative technologies, and reinforcing the constraints of the dual-carbon target.

Evaluating the sustainable features of vernacular architecture in hot-arid regions: field surveys and analysis in two vernacular houses in Al Batinah region (Oman)

ABSTRACT The necessity to derive sustainable building solutions from the local vernacular architecture is being increasingly asserted in the global debate about the immense energy consumption, natural resources depletion, and high levels of Green House Emissions (GHG). Paradoxically, a limited number of research has addressed this issue in the arid hot regions and much less in the Arabian Peninsula. As a contribution to this debate, the present paper evaluates the sustainable features present in the Omani vernacular houses and their efficacy in terms of thermal comfort and energy performance. A Methodology that combines on-site measurements with modelling simulations, using DesignBuilder software, was applied to achieve the three objectives assigned to this study: (a) Characterization of Vernacular Architecture in Oman and its bioclimatic features, (b) Evaluation of the thermal and energy performance of a selected vernacular house. (c) A comparison of thermal and energy performance between a vernacular dwelling and a contemporary Omani house. The numerical simulation confirmed that the vernacular construction system provides enhanced thermal performance when compared to its modern counterpart. It has also been showed that the house with a vernacular construction system requires twice less cooling energy than its modern counterpart.

Numerical Investigation of a Heavy-Duty Compression Ignition Engine Converted to Ammonia Spark-Ignition Operation

Abstract Global decarbonization requires the increased use of zero-carbon fuels. Compared to hydrogen, ammonia is easier to store, transport, and produce. In addition, products of complete combustion of ammonia are water and nitrogen. Therefore, ammonia is an ideal green fuel for internal combustion engines. Drawbacks relate to the high ignition energy and low laminar flame speed of ammonia. This three-dimensional numerical study investigated the potential of converting existing diesel engines to ammonia spark ignition operation. Results indicated a slower kernel inception process, but the speed of the fully developed turbulent flame was enough to complete the bulk combustion process despite the lower laminar flame speed. The problem with pure ammonia operation was the reduced combustion efficiency and the high level of unburned ammonia emissions since the slow spark inception process can be compensated by a larger compression ratio. The results also suggested that emissions formation and subsequent oxidation were a more complex phenomenon. For example, lean ammonia combustion produced higher nitrogen oxides (NOX) concentrations due to the nitrogen in the fuel, despite the lower combustion temperature. Moreover, advancing spark timing reduced the NOX emissions, which was opposite to the traditional spark ignition engines. Additionally, the ammonia in engine crevices that escaped the late oxidation process was the main source of nitrous oxide (N2O) species in the exhaust gas that usually do not appear in traditional engines. Overall, all these results suggested that more fundamental research on ammonia combustion is needed to understand its use in efficient, decarbonized engines.

Past and future changes in the start, end, and duration of the growing season in Poland

The aim of the study was to determine the direction and rate of the projected changes of the start, end, and duration of the growing season in Poland in two-time horizons: 2021–2050 and 2071–2100. The main part of the paper was preceded by an analysis of changes in the start and end dates and the duration of the growing season in Poland in the period 1966–2020. The growing season in Poland is projected to be the shortest in mountain areas and in the north-eastern regions of Poland, where the date of growing season start is the latest and the date of the growing season end is the earliest. Whereas the longest growing season due to the projected earliest start and latest end dates is expected in the southwestern Poland. In the case of the coast, its late end will be of the greatest importance for its duration as a result of the warming effect of the sea in the autumn–winter period. The most intensive changes are forecasted in the long-term perspective in the case of the scenario regarding a high level of greenhouse gas emissions. The forecasts show that outside mountain areas, the growing season duration will vary from less than 255 days in the northeastern regions to more than 290 days in southwest and western Poland. In the duration of the mountains, the growing season will vary from 180 days on Kasprowy Wierch to 188 days on Śnieżka. This suggests significant changes in agroclimatic conditions in Poland.

Review and Evaluation of Reinforcement Learning Frameworks on Smart Grid Applications

With the rise in electricity, gas and oil prices and the persistently high levels of carbon emissions, there is an increasing demand for effective energy management in energy systems, including electrical grids. Recent literature exhibits large potential for optimizing the behavior of such systems towards energy performance, reducing peak loads and exploiting environmentally friendly ways for energy production. However, the primary challenge relies on the optimization of such systems, which introduces significant complexities since they present quite dynamic behavior. Such cyberphysical frameworks usually integrate multiple interconnected components such as power plants, transmission lines, distribution networks and various types of energy-storage systems, while the behavior of these components is affected by various external factors such as user individual requirements, weather conditions, energy demand and market prices. Consequently, traditional optimal control approaches—such as Rule-Based Control (RBC)—prove inadequate to deal with the diverse dynamics which define the behavior of such complicated frameworks. Moreover, even sophisticated techniques—such as Model Predictive Control (MPC)—showcase model-related limitations that hinder the applicability of an optimal control scheme. To this end, AI model-free techniques such as Reinforcement Learning (RL) offer a fruitful potential for embedding efficient optimal control in cases of energy systems. Recent studies present promising results in various fields of engineering, indicating that RL frameworks may prove the key element for delivering efficient optimal control in smart buildings, electric vehicle charging and smart grid applications. The current paper provides a comprehensive review of RL implementations in energy systems frameworks—such as Renewable Energy Sources (RESs), Building Energy-Management Systems (BEMSs) and Electric Vehicle Charging Stations (EVCSs)—illustrating the benefits and the opportunities of such approaches. The work examines more than 80 highly cited papers focusing on recent RL research applications—between 2015 and 2023—and analyzes the model-free RL potential as regards the energy systems’ control optimization in the future.

Sustainable Management of Bio Medical Waste in Chennai: A case study

The aim of the current research article is to study various treatment techniques involved in the management of bio medical waste and select the most appropriate treatment method in terms of cost savings, energy recovery and waste volume reduction in a sustainable manner. Most of the HCF (Health Care Facilities) lacks the provision for on-site waste treatment facility. One of the major reasons might be the fear of high pollutant emission levels from multiple machines or equipment used in the treatment process. At times, it could be due to lack of sufficient space within the clinical premises. To overcome this situation, a minor amendment has to be introduced in the bio medical waste management rules 2016, which includes providing a suitable area necessary for medical waste treatment within the premises, during the construction stage itself. Further, the identification of appropriate treatment techniques based on the type of waste generated is also important. Even a primary HCF too should be equipped with the requisite treatment facilities, considering the emission levels to be within the standards. This sort of installing an on-site waste treatment facility will reduce the amount spent upon external agencies for disposal and treatment of the medical waste. Then, the leftover residue is securely landfilled in the dedicated site or even be liable to mix with the municipal solid garbage. The current study concludes that the implementation of one of the treatment techniques in a specific hospital helps in energy recovery, huge reduction in the volume of waste generation and avoids illegal dumping of the waste, thereby creating less impact on the surrounding environment.

Investigating the influence of plastic waste oils and acetone blends on diesel engine combustion, pollutants, morphological and size particles: Dehalogenation and catalytic pyrolysis of plastic waste

Most research into the treats of plastic wastes have concentrated mainly on single-exposure pathways or products. These practices fail to acknowledge that the complications of carbon particles from engines are produced not only by diesel but by any plastic oils due to the vast amount of contaminants. With the potential to significantly weaken the impact of contaminants, the present study investigates the effects of dehalogenation and catalytic pyrolysis on plastic waste, as well as the risks associated with plastic oil blends on diesel engine. Different types of washing were conducted to effectively dehalogenate plastic waste. After pretreatment, odor compounds were analyzed using GC–MS. Subsequently, various types of pretreated plastic samples underwent catalytic pyrolysis with a 5:1 ratio of HDPE to Al2O3·2SiO2·2H2O. Differences in physico-chemical properties and hydrocarbon compounds of oils were determined. Experiments were performed using different fuel blends in a diesel engine under steady-state conditions, and their effects on combustion, emissions, morphology, and size particles were analyzed. The results show that sample B exhibited a lower toxicity level of 1,3-butadiene compared to other samples, while acetone and terpenes represented the second and third-highest emission levels in flakes, respectively. Sample C started to degrade at low temperatures (<300 °C) due to carbon addition from ethyl acetate solvent into the tertiary carbon chain of the flakes. DAP3 fuel achieved a higher reaction due to its degree of unsaturation and lower viscosity, resulting in the formation of smaller fuel droplets at high injection pressure and heat release rate (HRR). Higher emission levels were observed by DAP1 and D100, exceeding the Euro 5/6 standard limits. However, DAP3 fuel resulted in an average reduction of ∼17.14% and 21.86% in CO and smoke emissions, respectively, accompanied by a slight decrease in NOx and HC levels. Conversely, there were inconsistencies in the emission results observed with DAP2. Compared to D100, both DAP1 and DAP2 exhibited a significant accumulation and coarse particles in the PM10 forms at a peak of ∼83 nm. Whereas the DAP3 showed a smaller mobility Dp with a low nucleation particle peak, which was prone to absorb the unburned HC soot and later change to accumulation mode particles.

Green Growth Analysis of Social Development in OECD Countries

This paper seeks to elucidate the inter and intrarelationships between a selected set of OECD green growth indicators (GGI). In addition to the selected GGI, the analysis includes the Human Development Index (HDI) and its sub-indicators. The novelty of the analysis comes from the incorporation of these established indicators, which have been utilised and developed to reflect human well-being and prosperity for decades. Production-based CO2 intensity and emission change are significantly correlated to average length of schooling across the 36 countries that were members of the OECD in the year 2019. Longer years spent in school on average can facilitate the green transition of countries. The correlations among intra-GGI also suggest where OECD countries are lagging in terms of green transition. For example, renewable energy supply share in energy and air transport-related CO2 per capita are positively correlated in the countries. This indicates that countries with a successful path toward green energy are not paying much attention to their high level of CO2 emissions caused by aviation. Infrastructural and technological advancement as well as increased public awareness are needed to challenge such issues.

Modelling environmental energy efficiency in the presence of carbon emissions: Modified oriented efficiency measures under polluting technology of data envelopment analysis

Reductions of carbon dioxide (CO2) emissions and energy consumption are two vital methods contributing in improvement of the environmental energy efficiency. Since data envelopment analysis (DEA) provides a synthetic standardised index of environmental efficiency through considering real factors, such as undesirable outputs and integer-valued data, it has acquired major popularity in environmental energy efficiency. Previous studies regarding applications of oriented DEA models to environmental efficiency did not consider the simultaneous impact of undesirable outputs under the polluting technology and mixed integer-valued data on efficiency measures. The objective of this research is to obtain comprehensive environmental energy efficiency measurements by extending the output-oriented slacks-based measure (SBM) model of Tone (2001) and the output-oriented BCC model of Banker et al. (1984). Thus, new output-oriented SBM and BCC models in mixed integer-valued data and undesirable outputs under the polluting technology are modelled. The models have been utilised to examine scale energy efficiency, pure energy efficiency, output mix-efficiency measure, carbon efficiency, and potential carbon reduction of 30 provinces in China to evaluate their land transportation systems. Additionally, the results are remarkable and interesting compared to those reported in Chang, Zhang, Danao, and Zhang (2013) since many provinces, performed environmental efficiency. There are 12 and 14 provinces, performed environmental output mix-efficiency under CRS and VRS, respectively. Moreover, 50% of the total evaluated provinces performed carbon efficiency. In regard of environmental-inefficient provinces, the proposed efficiency measures showed that provinces produce high levels of carbon emissions have risky potential to save energy.

Dramatic loss of seagrass Zostera marina L. suitable habitat under projected climate change in coastal areas of the Bohai Sea and Shandong peninsula, China

Seagrass is an important foundational species in marine ecosystems that plays an important role in providing ecosystem services. However, seagrass distribution and suitable habitat have rapidly declined in recent decades because of climate change and human-mediated disturbances. To achieved better conservation and management of the seagrass Zostera marina, an important representative seagrass in northern China, studies must investigate how this species responds to climate change. Here, we used an ensemble species distribution model to forecast the potential distribution and future suitable habitat change for the eelgrass Z. marina in coastal areas of the Bohai Sea and Shandong Peninsula, China. Two future climate scenarios, RCP 4.5 and RCP 8.5, were considered, which represent stable and high levels of greenhouse gas emissions, respectively. The ensemble model accurately predicted the current Z. marina distribution and performed better than the single-algorithm methods of random forest, generalized boosting model and maximum entropy according to performance matrices (AUC and TSS). The distance to land (78.50 ± 3.51%) and the maximum sea surface temperature (11.90 ± 0.25%) were the most important variables determining the distribution of Z. marina, while the contributions of other variables, maximum sea surface current velocity (3.80 ± 0.33%), minimum surface salinity (2.15 ± 0.22%) and water depth (1.74 ± 0.24%) were relatively low. Under future climate scenarios, the suitable habitat of Z. marina was predicted to decrease by more than half by the 2050s, whereas under the pessimistic greenhouse gas emission scenario (RCP 8.5), suitable Z. marina habitat was predicted to decrease by nearly 80% by the end of this century. The loss of Z. marina seagrass beds will have important ecological effects on the marine ecosystem. Our results not only provide valuable information to assist in identifying potential Z. marina meadows, but also have important implications for guiding conservation and management of Z. marina in the northern coastal region of China.

Financial innovation and environmental quality: Fresh empirical evidence from the EU Countries.

Evidence shows that the European Union (EU) is a leader in using financial innovation to overcome environmental challenges and ensure sustainable development. This study explores the heterogeneous effects of financial innovations on carbon dioxide emissions (CO2) due to their destructive effects in the context of the EU, by employing the novel Method of Moments Quantile Regression (MM-QR). The study also evaluates the environmental Kuznets hypothesis during the period of 2000-2020. We used four proxies for financial innovation; the ratio of the aggregate money supply to narrow money (M3/M1), the ratio of broad to narrow money (M2/M1), the percentage change in domestic credit to the private sector (% of GDP) and a composite index of these indices using the Principal Component Analysis technique. The findings indicate that raising three financial innovation proxies can effectively raise environmental quality. It should be noted that while M3/M1 has a stronger and negative effect on CO2 emissions in low quantiles, M2/M1 has a stronger and negative effect on CO2 emissions in high quantiles. Therefore, it is recommended that a larger amount of M2 and M3 resources be directed towards green projects for financing in countries with both high and low levels of CO2 emissions, respectively.

Green Technological Progress Implications on Long-Run Sustainable Economic Growth

The main objective of this study is to model and examine the green technological progress’s positive and negative externalities spillover effects on the sustainable economic growth of 15 economies from Asia, the Pacific, and Latin America. The study calculated labour and capital contributions to green total factor productivity growth via the inclusion of CO2 emissions as undesirable output or private unpriced input and energy consumption that proxies for unmeasured pollutant emissions. The results, in most cases, confirm that a high level of air pollutant emissions generated by these countries’ economic development affected the growth rates of TFP growth as an indicator of green technological progress. The significant contribution of this study is to integrate innovation and climate change in the form of green productivity (green technological progress). The role of these externalities on long-term sustainable economic growth has been ignored by several past studies undertaken in these areas.

The effect of pure methane energy fraction on combustion performance, energy analysis and environmental - economic cost indicators in a single-cylinder common rail methane-diesel dual fuel engine

Although methane-diesel dual fuel implementation is a very effective method in reducing high NOx and smoke emissions, which are the main problems of diesel engines, this implementation still suffers from high level of HC and CO emissions at low-medium load conditions. Considering this problem of dual-fuel engines, it is very important to examine the effects of pollutant emissions resulting from combustion on the environment and human health to see the usability of methane gas in dual fuel mode, and the current literature is quite limited. Therefore, in this study, the effect of methane energy fraction on combustion, emissions and environmental-economic costs was investigated in a dual fuel engine with optimum diesel injection timing.The tests were conducted in a single-cylinder, air-cooled, common rail diesel engine at constant engine speed and variable engine loads. The operation was carried out in two different modes as diesel and methane-diesel dual fuel. In the first mode, the optimum diesel injection timing of common rail diesel engine was determined. Five different injection timings from 11°CA to 19°CA before top dead center (bTDC) were used to determine the optimum diesel injection timing. The second mode was carried out at varying methane energy fraction (MEF) levels with %0, %25, and %50 contributions to the total fuel energy of methane. In the optimum injection timing experiments, the lowest ignition delay period, combustion duration, lower emission values, and better engine performance were obtained with 11°CA bTDC under all load conditions. The methane energy fraction significantly reduced the maximum combustion pressure, especially under low load conditions. However, combustion pressure values of diesel and methane-diesel dual fuel studies under high load conditions were obtained close to each other due to late injection timing, high injection pressure, and higher combustion temperature. Moreover, COVIMEP values of all test fuels were obtained below 5% under medium and high load conditions. On the other hand, NO and smoke emissions, which are the main problems of diesel engines, decreased significantly. With the increase of MEF level in methane-diesel dual fuel application, NO emissions showed an improvement up to 67%. Similarly, smoke emissions improved up to 82%. Despite the high HC and CO emissions, which is one of the main problems of the dual fuel mode, the significant reduction of NO emissions due to methane addition has significantly improved the environmental and economic costs. This situation clearly demonstrated the usability of high methane substitution in terms of emissions in dual fuel mode. In addition, exhaust energy loss for all load conditions in methane-diesel dual fuel mode showed an average improvement of 13.5% compared to diesel mode. As a result, high methane substitution is promising because it significantly reduces NO and smoke emissions, which are the main problems of diesel engines, and the low-performance data is at a compensable level.

Micro-macro multilevel analysis of day-to-day lifestyle and carbon emissions in UK multiple occupancy households

Far-reaching changes in daily life present a pressing need to balance energy consumption with environmental impact. Previous research on household carbon emissions generally described its contributors in disposable income, consumption pattern, and household-related lifestyle, whereas they have not fully explored how carbon emissions relate to residents' day-to-day lifestyles. Given that individual lifestyles within a household may be correlated, there is a need to disentangle the clustering effect of household members' lifestyles and their association with household carbon emissions. This study used micro-macro multilevel modelling to examine the structure of individual lifestyles and their impact on household carbon emissions for 8618 multiple occupancy households of 19,816 respondents in the UK Household Longitudinal Study dataset. The results showed that a factor capturing energy-saving lifestyle behaviours significantly reduced housing fuel use emissions and a second capturing transportation and consumption choices cut motor emissions. Interestingly, the contribution of energy-saving lifestyle in cutting down housing-fuel-using emissions becomes more pronounced when household income and household characteristics (e.g., household size, dwelling, house ownership, number of cars, urbanity, employment) were controlled for. Contrarily, the strength of green transportation and consumption lifestyle contributing to lower motor emissions was weakened after controlling for household characteristics. Findings indicated that day-to-day lifestyle not only reflects individual variability in sustainable living but also systematic household variation in carbon emissions. Knowledge of which living patterns are responsible for disproportionately high levels of carbon emissions can enhance effective targeted policy aimed at stimulating sustainable lifestyles and carbon reduction.

Effect of ventilation on carbon monoxide and soot particles emissions in a confined and mechanically-ventilated fire

Fire behavior in a 1 m3 confined and mechanically ventilated compartment is investigated experimentally. The main objective is to study carbon monoxide and soot particle emissions by four different fuels: pure n-heptane, technical-grade dodecane, kerosene Jet A-1, and Mobil DTE oil heavy medium. Air Renewal rates are set at 4.83 ACH, 9.67 ACH, and 17.8 ACH, while the fuel pan diameters are 0.115 m, 0.14 m, and 0.19 m. The results show that decreasing the renewal rate or increasing the pan size decreases the mass loss rate and soot emissions. However, CO emissions increase. Lighter fuels exhibit higher mass loss rates and CO emissions than heavier fuels. The highest smoke temperatures are produced at high renewal rates and large pan diameters. Meanwhile, soot emission levels decrease in the order of kerosene > dodecane > Mobil oil > heptane. High levels of soot but low CO emissions are present in well-ventilated fires. However, high CO but low soot emissions appear in under-ventilated fires. The soot particles collected in the smoke layer show unimodal distribution. The modal diameter of the particles ranges from 220 nm to 300 nm.

Paris Agreement could prevent regional mass extinctions of coral species.

Coral reef ecosystems are expected to undergo significant declines over the coming decades as oceans become warmer and more acidic. We investigate the environmental tolerances of over 650 Scleractinian coral species based on the conditions found within their present-day ranges and in areas where they are currently absent but could potentially reach via larval dispersal. These "environmental envelopes" and connectivity constraints are then used to develop global forecasts for potential coral species richness under two emission scenarios, representing the Paris Agreement target ("SSP1-2.6") and high levels of emissions ("SSP5-8.5"). Although we do not directly predict coral mortality or adaptation, the projected changes to environmental suitability suggest considerable declines in coral species richness for the majority of the world's tropical coral reefs, with a net loss in average local richness of 73% (Paris Agreement) to 91% (High Emissions) by 2080-2090 and particularly large declines across sites in the Great Barrier Reef, Coral Sea, Western Indian Ocean, and Caribbean. However, at the regional scale, we find that environmental suitability for the majority of coral species can be largely maintained under the Paris Agreement target, with 0%-30% potential net species lost in most regions (increasing to 50% for the Great Barrier Reef) as opposed to 80%-90% losses under High Emissions. Projections for subtropical areas suggest that range expansion will give rise to coral reefs with low species richness (typically 10-20 coral species per region) and will not meaningfully offset declines in the tropics. This work represents the first global projection of coral species richness under oceanic warming and acidification. Our results highlight the critical importance of mitigating climate change to avoid potentially massive extinctions of coral species.

Analyzing the spatiotemporal carbon change mechanism: a land-based carbon flow network (CFN) for cities

High carbon emissions played a significant role in global climate change, which made cities with rapid urbanization responsible for local carbon mitigation. In this study, a land-based CFN framework was established by taking 15 land use types as different network nodes. The framework was intended to be a dynamic structure containing the carbon emissions/sequestration tracking, land-based carbon network and utility analysis, and carbon change mechanism identification. By taking Guangzhou city as an empirical study, the carbon metabolism patterns were shown as increasing emission expansion and spatial differentiation. The high-level emission patches extended from the city center to the suburb with 1/2 to 1/3 the original size from 2000 to 2020, which featured as land use transition toward T in the north and to C2 in the south. All the changing carbon processes among land nodes were detected to conduct CFN utility analysis for mechanism investigation. Exploitation was found significantly contributed to the carbon emissions in 2000-2005 and fell over time. In the built-up area, the dominant carbon relationship has changed from exploitation to mutualism with enlarged carbon emissions in 2000-2005, 2005-2010, and 2010-2015, and the exploitation became dominant in 2015-2020 with increasing carbon sequestration. Under the increasing competitive relationship, carbon emissions of the related land nodes decreased more than 90% from 2000 to 2020 with favorable mutual restriction between pairwise nodes. It provided valuable insight for the carbon mitigation options at a city level through local urban planning.