Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53

Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO2 emissions and non-CO2 impacts, such as NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NOx emitted, or per flown kilometre.In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NOx-induced ozone and H2O effects are well represented by the ACCF model output. The NOx-induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NOx-induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NOx-induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO2 contribution observed in this study is low compared with the non-CO2 effects, which requires further diagnosis.

Simulation Study on Airflow Organization and Environment in Reconstructed Fangcang Shelter Hospital Based on CFD

With frequent outbreaks of COVID-19, the rapid and effective construction of large-space buildings into Fangcang shelter hospitals has gradually become one of the effective means to control the epidemic. Reasonable design of the ventilation system of the Fangcang shelter hospital can optimize the indoor airflow organization, so that the internal environment can meet the comfort of patients and at the same time can effectively discharge pollutants, which is particularly important for the establishment of the Fangcang shelter hospital. In this paper, through the reconstruction of a large-space gymnasium, CFD software is used to simulate the living environment and pollutant emission efficiency of the reconstructed Fangcang shelter hospital in summer under different air supply temperatures, air supply heights and exhaust air volume parameters. The results show that when the air supply parameters are set to an air supply height of 4.5 m, an air supply temperature of 18 °C, and an exhaust air volume of a single bed of 150 m3/h, the thermal comfort can reach level I, and the ventilation efficiency for pollutants can reach 69.6%. In addition, the ventilation efficiency is 70.1% and 70.3% when the exhaust air volume of a single bed is continuously increased to 200 and 250 m3/h, which can no longer effectively improve the pollutant emission and will cause an uncomfortable blowing feeling to patients. © 2023 by the authors.

Anomalies of O3, CO, C2H2, H2CO, and C2H6 detected with multiple ground-based Fourier-transform infrared spectrometers and assessed with model simulation in 2020: COVID-19 lockdowns versus natural variability

Anomalies of tropospheric columns of ozone (O3), carbon monoxide (CO), acetylene (C2H2), formaldehyde (H2CO), and ethane (C2H6) are quantified during the 2020 stringent COVID-19 world-wide lockdown using multiple ground-based Fourier-transform infrared spectrometers covering urban and remote conditions. We applied an exponential smoothing forecasting approach to the data sets to estimate business-as-usual values for 2020, which are then contrasted with actual observations. The Community Atmosphere Model with chemistry (CAM-chem) is used to simulate the same gases using lockdown-adjusted and business-as-usual emissions. The role of meteorology, or natural variability, is assessed with additional CAM-chem simulations. The tropospheric column of O3 declined between March and May 2020 for most sites with a mean decrease of 9.2% ± 4.7%. Simulations reproduce these anomalies, especially under background conditions where natural variability explains up to 80% of the decline for sites in the Northern Hemisphere. While urban sites show a reduction between 1% and 12% in tropospheric CO, the remote sites do not show a significant change. Overall, CAM-chem simulations capture the magnitude of the anomalies and in many cases natural variability and lockdowns have opposite effects. We further used the long-term record of the Measurements of Pollution in the Troposphere (MOPITT) satellite instrument to capture global anomalies of CO. Reductions of CO vary highly across regions but North America and Europe registered lower values in March 2020.The absence of CO reduction in April and May, concomitant with reductions of anthropogenic emissions, is explained by a negative anomaly in the hydroxyl radical (OH) found with CAM-chem.The implications of these findings are discussed for methane (CH4), which shows a positive lifetime anomaly during the COVID-19 lockdown period. The fossil fuel combustion by-product tracer C2H2 shows a mean drop of 13.6% ± 8.3% in urban Northern Hemisphere sites due to the reduction in emissions and in some sites exacerbated by natural variability. For some sites with anthropogenic influence there is a decrease in C2H6.The simulations capture the anomalies but the main cause may be related to natural variability. H2CO declined during the stringent 2020 lockdown in all urban sites explained by reductions in emissions of precursors. Copyright: © 2023 The Author(s).

IMPLICATIONS OF POTENTIAL NEW REGULATORY MEASURES TO ADDRESS AVIATION EMISSIONS

This work is an analysis of the implications of the potential new regulatory policies being recently proposed in the European Union, in particular the mandatory blending of SAF (on top of the already existing CORSIA or ETS), to address aviation emissions from a technical, operational and economic perspective. As a continuation of previous work from the Department of Aerospace Systems, Air Transport and Airports from the ETSIAE (Universidad Politécnica de Madrid), the air traffic structure of the European Union in 2019 has been analysed based on publicly available data from EUROCONTROL and EUROSTAT. The output has been used as the reference scenario for the implementation of the mandatory blending of SAF, expected to take over at the beginning of 2025, since it is expected that by then, air traffic will reach the pre-COVID levels. The results show that all the policy options considered so far have uneven impact among the different stakeholders and that before deciding going forward with any of the presented options, extra work needs to be done to overcome the different challenges that would potentially arise. © 2022 ICAS. All Rights Reserved.

A Review on Solar Energy Policy and Current Status: Top 5 Countries and Kazakhstan

The article describes the world's experience in developing the solar industry. It discusses the mechanisms of state support for developing renewable energy sources in the cases of five countries that are the most successful in this area—China, the United States, Japan, India, and Germany. Furthermore, it contains a brief review of state policy in producing electricity by renewable energy facilities in Kazakhstan. This paper uses statistical information from the International Renewable Energy Agency (IRENA), the International Energy Agency (IEA), British Petroleum (BP), and the Renewable Energy Network (REN21), and peer-reviewed sources. The research methodology includes analytical research and evaluation methods to examine the current state of solar energy policy, its motivators and incentives, as well as the prospects for its development in Kazakhstan and in the world. Research shows that solar energy has a huge development potential worldwide and is sure to take its place in gross electricity production. This paper focuses on the selected economic policies of the top five countries and Kazakhstan, in what may be considered a specific research limitation. Future research suggestions for the expansion of Renewable Energy (RE) in Kazakhstan could include analysing the impact of introducing dedicated policies and incentives for solar systems and exploring the benefits and challenges of implementing large RE zones with government–business collaboration.

Can We Detect Urban‐Scale CO2 Emission Changes Within Medium‐Sized Cities?

The COVID‐19 pandemic resulted in a widespread lockdown during the spring of 2020. Measurements collected on a light rail system in the Salt Lake Valley (SLV), combined with observations from the Utah Urban Carbon Dioxide Network observed a notable decrease in urban CO2 concentrations during the spring of 2020 relative to previous years. These decreases coincided with a ∼30% reduction in average traffic volume. CO2 measurements across the SLV were used within a Bayesian inverse model to spatially allocate anthropogenic emission reductions for the first COVID‐19 lockdown. The inverse model was first used to constrain anthropogenic emissions for the previous year (2019) to provide the best possible estimate of emissions for 2020, before accounting for emission reductions observed during the COVID‐19 lockdown. The posterior emissions for 2019 were then used as the prior emission estimate for the 2020 COVID‐19 lockdown analysis. Results from the inverse analysis suggest that the SLV observed a 20% decrease in afternoon CO2 emissions from March to April 2020 (−90.5 tC hr−1). The largest reductions in CO2 emissions were centered over the northern part of the valley (downtown Salt Lake City), near major roadways, and potentially at industrial point sources. These results demonstrate that CO2 monitoring networks can track reductions in CO2 emissions even in medium‐sized cities like Salt Lake City.Alternate :Plain Language SummaryHigh‐density measurements of CO2 were combined with a statistical model to estimate emission reductions across Salt Lake City during the COVID‐19 lockdown. Reduced traffic throughout the COVID‐19 lockdown was likely the primary driver behind lower CO2 emissions in Salt Lake City. There was also evidence that industrial‐based emission sources may of had an observable decrease in CO2 emissions during the lockdown. Finally, this analysis suggests that high‐density CO2 monitoring networks could be used to track progress toward decarbonization in the future.

Investigating the impact of COVID-19 on sustainable food supply chains

PurposeThe ongoing pandemic has gravely affected different facets of society and economic trades worldwide. During the outbreak, most manufacturing and service sectors were closed across the globe except for essential commodities such as food and medicines. Consequently, recent literature has focused on studying supply chain resilience and sustainability in different pandemic contexts. This study aims to add to the existing literature by exploring the economic, environmental and societal aspects affecting the food supply chain and assessing the impact of COVID-19 on food sustainability.Design/methodology/approachA survey method has been adopted with a questionnaire instrument investigating the role of technology, government policies, geopolitics and intermediaries on sustainable organisational management. A five-point Likert scale (i.e. 1 = strongly disagree;5 = strongly agree) is used to evaluate the responses. The findings are based on 131 responses from entry-level workers and senior executives of different food supply chains across Asia and Europe. The data has been analysed to derive insights into the impacts of this pandemic.FindingsThe survey concludes with the significant impact of COVID-19 on the three pillars of sustainability, i.e. economic, social and environmental dimensions. The empirical analysis shows digitalisation and its applications help mitigate the negative effect of COVID-19 on sustainability. In addition, the supportive government policies and intermediatory interventions were helpful in improving sustainability at each level.Research limitations/implicationsThe findings have implications for businesses and policymakers. Companies can learn from the advantages of digitalisation to counter the challenges imposed by the pandemic or similar situations in the future in maintaining the sustainability of their supply chains. Managers can also learn the importance of effective organisational management in driving sustainability. Finally, policymakers can devise policies to support businesses in adopting sustainable practices in their supply chains.Originality/valueThis study adds to the limited literature exploring the impact of COVID-19 on food supply chain sustainability through the triple bottom line lens. To the best of the authors' knowledge, this is also one of the first empirical studies to examine the effect of technology, government and organisational management practices on the sustainability of food supply chains.

Unbalanced emission reductions of different species and sectors in China during COVID-19 lockdown derived by multi-species surface observation assimilation

The unprecedented lockdown of human activities during the COVID-19 pandemic has significantly influenced social life in China. However, understanding the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air-pollutant inversion system to simultaneously estimate the emissions of NOx, SO2, CO, PM2.5 and PM10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorological variations during the COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations in multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measure with NOx emissions decreasing substantially by ∼40 %. However, emissions of other air pollutants were found to only decrease by∼10% because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM2.5 concentrations occurred over the North China Plain (NCP) during the lockdown period, the emission change only accounted for 8.6 % of PM2.5 reductions and even led to substantial increases in O3. The meteorological variation instead dominated the changes in PM2.5 concentrations over the NCP, which contributed 90 % of the PM2.5 reductions over most parts of the NCP region. Meanwhile, our results suggest that the local stagnant meteorological conditions, together with inefficient reductions of PM2.5 emissions, were the main drivers of the unexpected PM2.5 pollution in Beijing during the lockdown period. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O3 and PM2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O3 and PM2.5 pollution in China.

Effects of COVID-19 on passenger shipping activities and emissions: empirical analysis of passenger ships in Danish waters

This paper focuses on the analysis of the COVID-19 effects on passenger shipping in Danish waters as an example and aims to analyse the differences in passenger vessel activities and emissions before and after the COVID-19 outbreak. Two sets of Automatic Identification System (AIS) data for the passenger ships sailing in Danish waters associated with the whole year respectively for 2020 and 2019 are used for a comprehensive evaluation of the passenger shipping activities in the region by means of the analysis of variance and bottom-up emission models. A comparison of those results based on the two datasets shows that the COVID-19 pandemic has a major impact on cruise ships, with a significant reduction in the number of ships, average speed, and average draught. In contrast, the pandemic has a smaller impact on ferry-pax only and ferry-ro pax vessels. The effects can also be seen from the fact that, after the COVID-19 outbreak, SOx emissions from cruise ships, ferry-pax only and ferry-ro pax vessels were reduced by 50.71%, 0.51% and 0.82%, respectively. This investigation provides an important reference for policy makers in the marine environment sector.

Quantification of oil and gas methane emissions in the Delaware and Marcellus basins using a network of continuous tower-based measurements

According to the United States Environmental Protection Agency (US EPA), emissions from oil and gas infrastructure contribute 30 % of all anthropogenic methane (CH4) emissions in the US. Studies in the last decade have shown emissions from this sector to be substantially larger than bottom-up assessments, including the EPA inventory, highlighting both the increased importance of methane emissions from the oil and gas sector in terms of their overall climatological impact and the need for independent monitoring of these emissions. In this study we present continuous monitoring of regional methane emissions from two oil and gas basins using tower-based observing networks. Continuous methane measurements were taken at four tower sites in the northeastern Marcellus basin from May 2015 through December 2016 and five tower sites in the Delaware basin in the western Permian from March 2020 through April 2022. These measurements, an atmospheric transport model, and prior emission fields are combined using an atmospheric inversion to estimate monthly methane emissions in the two regions. This study finds the mean overall emission rate from the Delaware basin during the measurement period to be 146–210 Mg CH4 h-1 (energy-normalized loss rate of 1.1 %–1.5 %, gas-normalized rate of 2.5 %–3.5 %). Strong temporal variability in the emissions was present, with the lowest emission rates occurring during the onset of the COVID-19 pandemic. Additionally, a synthetic model–data experiment performed using the Delaware tower network shows that the presence of intermittent sources is not a significant source of uncertainty in monthly quantification of the mean emission rate. In the Marcellus, this study finds the overall mean emission rate to be 19–28 Mg CH4 h-1 (gas-normalized loss rate of 0.30 %–0.45 %), with relative consistency in the emission rate over time. These totals align with aircraft top-down estimates from the same time periods. In both basins, the tower network was able to constrain monthly flux estimates within ±20 % uncertainty in the Delaware and ±24 % uncertainty in the Marcellus. The results from this study demonstrate the ability to monitor emissions continuously and detect changes in the emissions field, even in a basin with relatively low emissions and complex background conditions.

Oxygen flow: How much do we know?

Introduction: Since the advent of Covid, oxygen has been the centre of discussion despite being the most important entity for the survival of human life. As various modes of its delivery has been in practice for a long time, using the non-rebreather mask has been a part of most guidelines for emergencies and hypoxia. This requires a higher flowrate of up to 15 l/min. Most flowmeters can deliver upto 75 l/min over the maximum calibrated mark.1 What may appear as a small rise from the maximum labelled mark can deliver more oxygen than required and result in wastage of oxygen or hide the severity of the patient's condition. Using this audit/ QIP we are trying to determine if the flowrates delivered are as per the prescription/protocol. Aim(s): To find out if the oxygen administration when it is prescribed at 15L/min is at the prescribed value and therefore quantify the amount of oxygen that is being wasted. Method(s): Data was collected randomly, observing the flow rates that the patients were receiving as prescribed or over the prescribed rate for those on non rebreather mask. Result(s): 54 observations were recorded from ED, ITU, AMU and theatre recovery across two hospitals. It was found that 57.4% of the patients were on flowrates more than the prescribed value. Conclusion & Discussion: More than half the patients requiring high flow rate of oxygen were on rates more than prescribed. This is potentially due to the lack of understanding of the calibration of the flowmeter. This results in the wastage of oxygen causing significant financial loss and an increase in the carbon dioxide emission impacting the environmental pollution. We plan to run an educational intervention for staff in these departments to emphasise the importance of administering drugs (including oxygen) as they are prescribed, and how easy it is to over administer oxygen.

Activity-based integrated modelling for assessing COVID-19 impacts on transport operations and emissions

This study combines an integrated transport, land-use, and energy (iTLE) modeling system with traffic microsimulation model and emission simulator for a holistic analysis of COVID-19 pandemic related changes in traffic flows and emissions. An activity-based travel demand model within iTLE informs pandemic traffic operation scenarios for traffic microsimulation modeling. Link-based simulation outputs inform a finer-grained emission estimation process within a MOtor Vehicle Emission Simulator. Results suggest that the overall network performance improves during lockdown as average delays and queue time decrease by 42.04% and 5.9% respectively compared to pre-COVID condition. Emission results reveal that GHG emissions significantly decrease (64%) in lockdown while it starts increasing gradually in post-pandemic period. Link-based emission analysis indicates that major arterial streets achieve a significant reduction in air pollutant emission. The findings of this study will help transportation planners, engineers, and policymakers to devise effective policies for the improvement of transport operations and emissions.

Modeling fuel consumption and emissions by taxis in Tabriz, Iran: uncertainty and sensitivity analyses.

Taxis pose a higher threat to global climate change and human health through air emissions. However, the evidence on this topic is scarce, especially, in developing countries. Therefore, this study conducted estimation of fuel consumption (FC) and emission inventories on Tabriz taxi fleet (TTF), Iran. A structured questionnaire to obtain operational data of TTF, municipality organizations, and literature review were used as data sources. Then modeling was used to estimate fuel consumption ratio (FCR), emission factors (EFs), annual FC, and emissions of TTF using uncertainty analysis. Also, the impact of COVID-19 pandemic period was considered on the studied parameters. The results showed that TTF have high FCRs of 18.68 L/100 km (95% CI=17.67-19.69 L/100 km), which are not affected by age or mileage of taxis, significantly. The estimated EFs for TTF are higher than Euro standards, but the differences are not significant. However, it is critical as can be an indication of inefficiency of periodic regulatory technical inspection tests for TTF. COVID-19 pandemic caused significant decrease in annual total FC and emissions (9.03-15.6%), but significant increase in EFs of per-passenger-kilometer traveled (47.9-57.3%). Annual vehicle-kilometer-traveled by TTF and the estimated EFs for gasoline-compressed natural gas bi-fueled TTF are the main influential parameters in the variability of annual FC and emission levels. More studies on sustainable FC and emissions mitigation strategies are needed for TTF.

Financial stability influence on climate risk, GHG emission, and green economic recovery of China.

This study examines the nexus between financial stability, climate risks, GHG emission mitigation, and green economic recovery of China. Financing efforts to protect against and reduce the hazards associated with climate change need to consider these risks and resources. Study used the Kalman technique of analysis for empirical inference. This research focuses on the carbon risk in China by employing a Kalman estimation approach. Although environmental mitigation was found to be important at 39%, financial strength and carbon hazards were considerable at 34%. Moreover, the report demonstrates the relationship between climatic threats and environmental drift in China, at a rate of 17%, emphasizing the need to address climate change issues. A state's fiscal health guarantees national economic security while pursuing green economic recovery initiatives. Researchers concluded that precise policy suggestions were needed to promote green economic development.

Cochlear Function in Adults Exposed to Severe Acute Respiratory Syndrome Coronavirus 2.

INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a viral infection with a wide variety of symptoms, including fever, coughing, sneezing, fatigue, and a loss of taste and smell. Moreover, there are some recent studies that investigate the effects of SARS-CoV-2 on hearing and auditory performance. With this current study, we investigate the early effects of the coronavirus disease on hair cells in the cochlea. METHODS: In the current study, there were 25 subjects (17 females, 8 males) who tested positive for polymerase chain reaction on nasopharyngeal swabs. They had reported normal auditory functions and no history of otology before SARS-CoV-2. To determine auditory functions, pure-tone audiometry, otoacoustic emissions (OAE) tests, and threshold equalizing noise (TEN) tests were used. RESULTS: Although the hearing thresholds increased at higher frequencies, they were within normal limits according to four-frequency pure-tone averages. All participants had normal OAE, and there were no detected dead regions for any of the subjects. Even so, there were significant increases in hearing thresholds in TEN. CONCLUSION: There is no cochlear dysfunction discovered by OAE and TEN in SARS-CoV-2-affected individuals. Nonetheless, the increase in hearing thresholds at higher frequencies, other than the pure-tone average frequencies detected by TEN, and the decrease in the presence of detected OAE could be related to deterioration in the basal part of the cochlea.

Predicting the Impact of Change in Air Quality Patterns Due to COVID-19 Lockdown Policies in Multiple Urban Cities of Henan: A Deep Learning Approach

Several countries implemented prevention and control measures in response to the 2019 new coronavirus virus (COVID-19) pandemic. To study the impact of the lockdown due to COVID-19 on multiple cities, this study utilized data from 18 cities of Henan to understand the air quality pattern change during COVID-19 from 2019 to 2021. It examined the temporal and spatial distribution impact. This study firstly utilized a deep learning bi-directional long-term short-term (Bi-LSTM) model to predict air quality patterns during 3 periods, i.e., COVID-A (before COVID-19, i.e., 2019), COVID-B (during COVID-19, i.e., 2020), COVID-C (after COVID-19 cases, i.e., 2021) and obtained the R-2 value of more than 72% average in each year and decreased MAE value, which was better than other studies' deep learning methods. This study secondly focused on the change of pollutants and observed an increase in Air Quality Index by 10%, a decrease in PM2.5 by 14%, PM10 by 18%, NO2 by 14%, and SO2 by 16% during the COVID-B period. This study found an increase in O-3 by 31% during the COVID-C period and observed a significant decrease in pollutants during the COVID-C period (PM10 by 42%, PM2.5 by 97%, NO2 by 89%, SO2 by 36%, CO by 58%, O-3 by 31%). Lastly, the impact of lockdown policies was studied during the COVID-B period and the results showed that Henan achieved the Grade I standards of air quality standards after lockdown was implemented. Although there were many severe effects of the COVID-19 pandemic on human health and the global economy, lockdowns likely resulted in significant short-term health advantages owing to reduced air pollution and significantly improved ambient air quality. Following COVID-19, the government must take action to address the environmental problems that contributed to the deteriorating air quality.

Valorization of hazardous plastic wastes into value-added resources by catalytic pyrolysis-gasification: A review of techno-economic analysis

Plastic waste pollution has grown exponentially since the 1950s. This situation was exacerbated when the volume of personal protective equipment (PPE)-based plastic waste surged after the COVID-19 pandemic. Plastic waste management such as landfills and incineration have adverse effects on the environment and human health due to the leaching of hazardous chemicals and the emission of toxic gases. Modern solutions such as biodegradable plastics and green brick technology are expensive and not well developed to valorize the current accumulation of plastic waste. This has led to the emergence of thermal degradation processes, which is faster and more realistic to solve the PPE-based plastic waste buildup. Pyrolysis and gasification systems to valorize plastic waste into hydrocarbons and fuels are discussed and compared with examples respectively. Scoping review approach is employed to conduct this study. To further increase the value of the final product of plastic waste management, the integrated pyrolysis system to upcycle plastic waste to carbon nanomaterials (CNMs) and the factors affecting the production of non-condensable gases are critically reviewed. The importance of feedstock composition, catalyst type, pyrolysis operating condition (including gas condition and temperature profiles) based on various studies is discussed. The potential and limitation of an integrated pyrolysis system are assessed from kinetic analysis, economic analysis and life-cycle assessment. This review is expected to contribute to the industrial-scale development of sustainable upcycling of plastic waste and enhance the production of desirable gas components for CNM synthesis for environmental sustainability.

The influence of COVID-19 pandemic on PM2.5 air quality in Northern Taiwan from Q1 2020 to Q2 2021.

The study aimed to investigate the PM2.5 variations in different periods of COVID-19 control measures in Northern Taiwan from Quarter 1 (Q1) 2020 to Quarter 2 (Q2) 2021. PM2.5 sources were classified based on long-range transport (LRT) or local pollution (LP) in three study periods: one China lockdown (P1), and two restrictions in Taiwan (P2 and P3). During P1 the average PM2.5 concentrations from LRT (LRT-PM2.5-P1) were higher at Fuguei background station by 27.9% and in the range of 4.9-24.3% at other inland stations compared to before P1. The PM2.5 from LRT/LP mix or pure LP (Mix/LP-PM2.5-P1) was also higher by 14.2-39.9%. This increase was due to higher secondary particle formation represented by the increase in secondary ions (SI) and organic matter in PM2.5-P1 with the largest proportion of 42.17% in PM2.5 from positive matrix factorization (PMF) analysis. A similar increasing trend of Mix/LP-PM2.5 was found in P2 when China was still locked down and Taiwan was under an early control period but the rapidly increasing infected cases were confirmed. The shift of transportation patterns from public to private to avoid virus infection explicated the high correlation of the increasing infected cases with the increasing PM2.5. In contrast, the decreasing trend of LP-PM2.5-P3 was observed in P3 with the PM2.5 biases of ∼45% at all the stations when China was not locked down but Taiwan implemented a semi-lockdown. The contribution of gasoline vehicle sources in PM2.5 was reduced from 20.3% before P3 to 10% in P3 by chemical signatures and source identification using PMF implying the strong impact of strict control measures on vehicle emissions. In summary, PM2.5 concentrations in Northern Taiwan were either increased (P1 and P2) or decreased (P3) during the COVID-19 pandemic depending on control measures, source patterns and meteorological conditions.