The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on air pollution levels. To investigate this issue, we propose an XGBoost-based model to predict the concentrations of PM2.5 and PM10 during the COVID-19 lockdown period in 2022, Shanghai, and thus explore the limits of anthropogenic emission on air pollution levels by comprehensively employing the meteorological factors and the concentrations of other air pollutants. Results demonstrate that actual observations of PM2.5 and PM10 during the COVID-19 lockdown period were reduced by 60.81% and 43.12% compared with the predicted values (regarded as the period without the lockdown measures). In addition, by comparing with the time series prediction results without considering meteorological factors, the actual observations of PM2.5 and PM10 during the lockdown period were reduced by 50.20% and 19.06%, respectively, against the predicted values during the non-lockdown period. The analysis results indicate that ignoring meteorological factors will underestimate the positive impact of COVID-19 lockdown measures on air quality. © 2023 by the authors.

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.

Research on the Optimal Energy Saving and Emission Reduction Path for Promoting High-Quality Industrial Development in Hubei Province

In December 2019, a novel coronavirus broke out in Wuhan City, Hubei Province, and, as the center of the coronavirus disease 2019 (COVID-19) epidemic, the economy and production throughout Hubei Province suffered huge temporary impacts. Based on the input–output and industrial pollution emissions data of 33 industrial industries in Hubei from 2010 to 2019, this article uses the non-parametric frontier analysis method to calculate the potential production losses and compliance costs caused by environmental regulations in Hubei's industrial sector by year and industry. Research has found that the environmental technology efficiency of the industrial sector in Hubei is showing a trend of increasing year-on-year, but the overall efficiency level is still not high, and there is great room for improvement. The calculation results with and without environmental regulatory constraints indicate that, generally, production losses and compliance costs may be encountered in the industrial sector in Hubei, and there are significant differences by industry. The potential production losses and compliance costs in pollution-intensive industries are higher than those in clean production industries. On this basis, we propose relevant policy recommendations to improve the technological efficiency of Hubei's industrial environment, in order to promote the high-quality development of Hubei's industry in the post-epidemic era.

Annual Variation of PM2.5 Chemical Composition in Ho Chi Minh City, Vietnam Including the COVID-19 Outbreak Period

PM2.5 was continuously collected in Ho Chi Minh City (HCMC), Vietnam, during the period from September 2019 to August 2020, which included the period of socioeconomic suppression caused by restrictions imposed in the face of the coronavirus disease of 2019. The concentrations of PM2.5 mass, water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) were determined to evaluate the seasonal variations in PM2.5, the effect of socioeconomic suppression on PM2.5, and potential PM2.5 sources in HCMC. The PM2.5 mass concentration during the sampling period was 28.44 +/- 11.55 mu g m(-3) (average +/- standard deviation). OC, EC, and total WSIs accounted for 30.7 +/- 6.6%, 9.7 +/- 2.9%, and 24.9 +/- 6.6% of the PM2.5 mass, respectively. WSOC contributed 46.4 +/- 10.1% to OC mass. NO3-, SO42-, and NH4+ were the dominant species in WSIs (72.7 +/- 17.7% of the total WSIs' mass). The concentrations of PM2.5 mass and total WSIs during the rainy season were lower than those during the dry season, whereas the concentrations of carbonaceous species during the rainy season were higher. The concentrations of PM2.5 mass and chemical species during the socioeconomic suppression period significantly decreased by 45%-61% compared to the values before this period. The OC/EC ratio (3.28 +/- 0.61) and char-EC/soot-EC (4.88 +/- 2.72) suggested that biomass burning, coal combustion, vehicle emissions, cooking activities are major PM2.5 sources in HCMC. Furthermore, the results of a concentration-weighted trajectory analysis suggested that the geological sources of PM2.5 were in the local areas of HCMC and the northeast provinces of Vietnam (where coal-fired power plants are located).

Research on cold chain logistics optimization model considering low-carbon emissions

Cold chain logistics distribution orders have increased due to the impact of COVID-19. In view of the increasing difficulty of route optimization and the increase of carbon emissions in the process of cold chain logistics distribution, a mathematical model for route optimization of cold chain logistics distribution vehicles with minimum comprehensive cost is established by considering the cost of carbon emission intensity comprehensively in this paper. The main contributions of this paper are as follows: 1) An improved hybrid ant colony algorithm is proposed, which combined simulated annealing algorithm to get rid of the local optimal solution. 2) Chaotic mapping is introduced in pheromone update to accelerate convergence and improve search efficiency. The effectiveness of the proposed method in optimizing cold chain logistics distribution path and reducing costs is verified by simulation experiments and comparison with the existing classical algorithms. © 2023 The Author(s). Published by Oxford University Press.

Tourism Development in Sub-Sahara Africa and Impact on Regional Airline Business Models

Tourism in Africa has experienced not only strong growth in terms of arrivals, but also in terms of expenditures and revenues and this has been driven primarily by a high number of international arrivals. The chapter examines some of Africa's high growth tourism markets with the largest international tourism receipts and compounded growth of approximately 6% per year. The chapter examines the multiple types of tourism and its economic benefit in terms of supporting national gross domestic product (GDP) growth. Tourism should be developed for its potential to enhance economies. Important aspects amongst tourism's benefits are that;it boosts economic regeneration;it offers a future, meaning that it holds out a promise for growth;it is one of the fastest growing economic activities;and it is a key driver towards economic growth. The tourism industry can provide considerable benefits to host communities through economic development, infrastructures development and as a medium for protecting the environment and culture. The chapter concludes by examining the future growth of the aviation industry, discusses international regulations and how this will affect tourism within the African region. The impact of COVID-19 on the tourism sector is revisited and discusses the overall impact on the travel and tourism industry. Finally, analysis on climate and environment is discussed and the International Civil Aviation Organization provides recommendations for the air transport industry to combat climate change and reduce carbon dioxide (CO2) emissions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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.

Getting to the STEM of Environmental Justice: Equity Causes Enrich Student Learning in Science Classrooms

From satellites to ground-based sensors, as well as mobile networks of monitors, the availability of massive data sets has increased the need for educating students in data literacy in order to ensure their competency in the global market (Bluhm et al. 2020;Gibson and Mourad 2018). The U.S. Environmental Protection Agency (EPA) defines environmental justice as, "... the fair treatment and meaningful involvement of all people regardless of race, color, national origin, or income, with respect to the development, implementation, and enforcement of environmental laws, regulations, and policies." According to Lacombe, more individuals die yearly from car exhaust (53,000) in the United States than road casualties (37,400). Students worked in groups to discuss their assumptions about factors they perceived to have an impact on air pollution levels (e.g., affluence, traffic, and vegetation).

Strategizing for Strength in EU PharmaN

"Though Europe's response has demonstrated strengths," the strategy document reports, "existing vulnerabilities have been thrown into sharp focus, including those related to data availability, the supply of medicines, or the availability of manufacturing capacities to adapt and support the production of medicines" (2). [...]a lot of the strategy's proposals stem from the European Green Deal, published in late 2019 (4), from which has emanated last year's EU industrial strategy (5). [...]setting up critical medicines production capacity in the EU would have to be compliant with the Union's competition rules and those of the World Trade Organization, the commission warned (2).

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.

A Bibliometric Analysis of Sustainable Food Consumption: Historical Evolution, Dominant Topics and Trends

The major goal of this study is to trace the emergence of SFC-related research across time, using a thematic map and a list of corresponding publications. In addition, this study aims to determine the author who has made the most significant contribution to this particular field. This study provides a comprehensive bibliometric analysis of the historical development and current trends in sustainable food consumption research, examining 2265 articles published between 1990 and 2023. Using the bibliometrics package of R Studio software version 4.2.1 and its Biblioshiny package, articles from the Scopus and Web of Science databases are examined. In the field of sustainable food consumption, we identify five distinct research phases: initial stagnation, infant growth, post-economic crisis, expanding phase and COVID-19 and post-pandemic. While research on broader sustainability topics can be traced back to the early 20th century, a very limited number of articles on sustainable food consumption was published in the 1990s. However, the number of publications increased incrementally over time, with a notable uptick in interest around 2015, and the subject was still being discussed in 2022. The emergence of the COVID-19 pandemic marked the beginning of the most recent phase of research, which analyzed the consumption patterns of consumers before and after the pandemic. Our study highlights key authors, documents and sources related to sustainable food consumption. The United States, Italy and the United Kingdom emerged as the most active contributors to the research on sustainable food consumption and were additionally the countries with the largest global market shares for organic products. Major sub-themes including organic food, food waste, sustainable development and food security, together with consumer behavior and organic products appeared as being the most researched sub-themes of recent times. The results of this study suggest that more research is related to sustainable food consumption in countries with a low organic food market share. In addition, the investigation of actual data on food waste, carbon footprints and greenhouse gas emissions resulting from food production and consumption is essential to gain holistic insights.

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.

The stock market and NO2 emissions effects of COVID‐19 around the world

In this paper, we study the impact of the coronavirus disease 2019 pandemic in estimated panel vector autoregression models for 92 countries. The large cross‐section of countries allows us to shed light on the heterogeneity of the responses of stock markets and nitrogen dioxide emissions as high‐frequency measures of economic activity. We quantify the effect of the number of infections and four dimensions of policy measures: (1) containment and closure, (2) movement restrictions, (3) economic support, and (4) adjustments of health systems. Our main findings show that a surprise increase in the number of infections triggers a drop in our two measures of economic activity. Propping up economic support measures, in contrast, raises stock returns and emissions and, thus, contributes to the economic recovery. We also document vast differences in the responses across subsets of countries and between the first and the second wave of infections.

The evaluation of government subsidy policies on carbon emissions in the port collection and distribution network: a case study of Guangzhou Port

The collection and distribution network of ports is the main cause of carbon emissions. The carbon peak is a basic policy in China, and the subsidy policy is one of the common measures used by the government to incentivize carbon reduction. We analyzed the transportation methods and the flow direction of a port and proposed a carbon emission calculation method based on emission factors. Based on the transportation time and the cost, a generalized transportation utility function was constructed, and the logit model was used to analyze the impacts of subsidy policies on transportation, thus calculating the effects of the subsidies on carbon reduction. We used Guangzhou Port as a case study, and calculated the carbon reduction effects in six different subsidy policy scenarios and concluded that the absolute carbon reduction value was proportional to the subsidy intensity. In addition, we constructed a subsidy carbon reduction efficiency index and found that the Guangzhou Port collection and distribution network had higher subsidy carbon reduction efficiency in low-subsidy scenarios. Finally, a sensitivity analysis was conducted on the subsidy parameters, and scenario 8 was found to have the highest subsidy carbon reduction efficiency. This achievement can provide decision support for the carbon emission strategy of the port collection and distribution network.

Assessing CO2 Emissions of Online Food Delivery in Japan

The COVID-19 pandemic and the subsequent lockdown of cities have led to the rapid growth of online food delivery (OFD). Moreover, there are concerns that OFD platforms may impose offers on users in order to continue to increase their market share, leading to numerous environmental issues such as overconsumption and a significant increase in plastic packaging waste. Most studies have focused on the environmental impacts associated with food packaging and have been mostly limited to China. However, less research has been carried out on the overall CO2 emissions of an OFD order including food. In this study, the CO2 emissions of an OFD order were assessed by considering the production, distribution, consumption and disposal of the ingredients, based on lifecycle thinking and existing secondary data, for three representative food groups (Western food, Japanese food and Chinese food) in Japan. This study found that the food production of an OFD order accounts for more than 70% of the CO2 emissions of the entire process, especially food ingredient production. Policy support and initiatives such as OFD platforms being able to serve different quantities of food based on actual consumer demand to avoid food waste, as well as changes in delivery methods, would help reduce the CO2 emissions of OFD. © 2023 by the authors.

INVESTIGATING THE CHANGE IN PREFERENCE OF LIVING AND TRANSPORT DURING COVID-19

The COVID-19 pandemic meant that people had to perform most of their daily activities from home. This study intends to investigate if a period of working from home has changed living preferences concerning housing size and location. The data was collected through a web-based survey. The literature is divided regarding the potential benefits of reduced commuting due to increased home office utilization. There is a prevalent risk of rebound effects as saved travel time might lead to increased travel on leisure, which could counterweight the benefits of reduced daily commuting in cities. Most of the respondents in this study want to work from home 2–3 days a week. The respondents that desire to move to a less central location state the lower square meter price as one important reason. Analyses in prevailing research did not investigate the preference for larger homes combined with increased home office use. Future studies should also investigate the desire for larger homes to achieve a holistic evaluation of the emissions related to telecommuting. © 2022 The Author(s). Licensed under a CC-BY 4.0 licence.

Antecedents of freight transportation for sustainable supply chain in the post-COVID era: an emerging market study

PurposeIn past years, the global supply chain has witnessed devastating effects of coronavirus (COVID-19) disease. However, the COVID-19 pandemic has renewed the interest of the Sustainable Supply Chain (SSC) stakeholders on sustainability. The stakeholders are now rethinking their business processes and strategy to make them sustainable. In this context, the relevant literature is required to support emerging markets to formulate sustainability-focussed strategies. The purpose of this study is to provide a comprehensive analysis of potential antecedents that leads towards sustainable development of freight transportation in emerging markets.Design/methodology/approachInitially, the antecedents of the Sustainable Freight Transport (SFT) system are derived from the literature survey followed by verification from the experts. Then, the potential antecedents are categorized under four (social, organizational, operational and environmental) broad categories. Afterwards, a Neutrosophic Analytic Network Process (N-ANP) method is employed to obtain the priority weights of the identified potential antecedents.FindingsThe paper identified and ranked 17 antecedents of the SFT system. According to the study's findings, the top three antecedents of SFT are "the presence of a multimodal transportation system,” "circularity in SFT” and "traffic congestion management”. The results from the study advocate the promotion of existing multi-modal transport facilities which is promising to achieve sustainability. The results suggested the adoption of the digital twin to manage the transport operations.Originality/valueThis study sheds light on how to achieve sustainability in the freight transportation system post-COVID era highlighting the potential antecedents. The study's findings will assist practitioners in developing SFT strategies in the face of such pandemics in future.

Strategies for implementation of green roofs in developing countries

PurposeReportedly, green roof (GR) makes a significant contribution towards a truly sustainable-built environment;however, its implementation is yet to hit a sufficient level in developing countries. Thus, this study assesses GR implementation strategies in developing countries by providing a comparative analysis through experts in Kazakhstan, Malaysia and Turkey.Design/methodology/approachThe study adopts a four-step methodological approach to achieve the research aim: literature review, focus group discussion, fuzzy analytical hierarchy process (FAHP) analysis and correlation analyses. First, a literature review followed by a focus group discussion is used to determine 18 (out of 25 initially) strategies for the selected context and these are classified into three categories: governmental and institutional support, knowledge and information and policy and regulation. Afterward, the identified GR strategies are evaluated using the FAHP with the data gathered from the experts in the countries studied. Finally, correlation analyses were used to observe the strength of agreement between the assessments of experts from the included countries.FindingsThe findings indicate that financial incentives, low-cost government loans and subsidies and tax rebates are the essential strategies for the wider adoption of GR. Evaluating the policy and regulations strategies also showed that mandatory GR policies and regulations and better enforcement of the developed GR policies are ranked as the most prominent strategies. The findings show a low level of agreement among respondents from Kazakhstan, while there is a high level of agreement between the experts in Malaysia and Turkey.Research limitations/implicationsThe research contribution is twofold. First (research implication), the study identifies the strategies through a complete literature review. Second, the identified strategies are evaluated through the lenses of experts in three developing countries which are hoped to provide (practical contribution) a better understanding of the most effective strategies that require attention and enable the frontline stakeholders (particularly government authorities) to focus on them.Originality/valueThe study findings provide a good point of departure to explore the strategies for broader adoption of GRs in developing economic setting.

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.