Annual Growth Rate Research Articles

Spatiotemporal dynamic evolution and influencing factors of land use carbon emissions: evidence from Jiangsu Province, China

Land use/cover change has an important impact on global climate change and carbon cycle, and it has become another major source of carbon emission after energy consumption. Therefore, this study focuses on the main line of “land use carbon emissions-spatial and temporal patterns-influencing factors,” and selects 13 cities in Jiangsu Province as the research object. Based on the data of land use and energy consumption, combined with the method of land use carbon emissions and ArcGIS technology, this study conducted a quantitative analysis of the spatio-temporal distribution of carbon emissions in Jiangsu Province. The factors affecting the spatial distribution of carbon emissions from land use in Jiangsu Province were discussed by using Geographic detector. The results show that: 1) Carbon emissions in Jiangsu Province showed an overall growth trend, from 16215.44 ×104tC in 2010–23597.68 ×104tC in 2020, with an average annual growth rate of 4.55%, of which the construction land and watersheds had a greater impact on carbon sources and sinks, respectively. 2) During the period, there were significant differences in carbon emission levels among different cities in Jiangsu Province, and the land use carbon emission in Jiangsu Province showed a stable spatial pattern of “northwest—southeast.” The southern part of Jiangsu is always the hot area of carbon emission, while the cold spot area is mainly distributed in the northern and central parts of Jiangsu. 3) The interaction of factors such as economic development, industrial structure, energy intensity, land use and human activities is an important reason for the spatio-temporal differences of land use carbon emissions in Jiangsu Province. Among them, the level of urbanization, population size and economic aggregate have significant effects on carbon emissions.

Export - Import performance of coal in India: Trends, challenges and measures for achieving trade balance

Coal is considered to be the one of the major and crucial natural resources in the world and in our Indian economy. Coal serves as the raw material for generation of the electricity, for the hotel industry and for the other purposes which are highly effective in our economy. Among the coal producers in the world, India is the fourth largest producer of coal and for the requirements of domestic uses India also imports the coal from different countries. In the Indian economy the amount of coal exports has resulted to the trade deficit problems. Although the Indian coal sector has shown a dominant performance, world bank research has shown some serious issues which are faced by the coal industry. Through this paper an attempt has been made to examine the trends, challenges and measures for achieving trade balance through various methods. In accordance to that, existing literature has been gathered with the topics consisting of Coal Exports and Coal Imports to illegal mining, innovative technology and foster ways which improve the quality of coal. The primary objective of this research articles aims in finding out the reasons which focuses for the huge imports and low imports of coal with an objective to achieve trade balance. Thus the conclusion is there are very uncharted areas which can be taken up by the researchers to find the trade balance of coal. For the statistical analysis the tools like Mann Whitney U - Test and Annual Growth Rate has been used using SPSS and the results are provided accordingly.

Production of Kombucha SCOBY Cellulose by Using Tea and Pumpkin Peel Waste as Fermentation Substrates: A Comparison Study

A market research survey by Technavio has estimated that the global market size of kombucha is projected to grow by USD 3.56 billion from 2021 to 2026 with a Compound annual growth rate (CAGR) value of 19.36%. Kombucha can generate new pellicle Symbiotic Culture of Bacteria and Yeast (SCOBY) that produces biopolymer of cellulose. The production of cellulose from fermentation of kombucha SCOBY has received great attention from scientists. The main objective of this preliminary study was to produce kombucha SCOBY cellulose (KSC) from tea and pumpkin peel waste as fermentation substrates. The carbohydrate and protein contents of both tea and pumpkin peel waste were determined by proximate analysis. The physicochemical properties of kombucha SCOBY cellulose (KSC) were studied using two spectroscopic techniques, namely Fourier Transform Infrared (FTIR) and X-Ray Diffraction (XRD). FTIR spectra revealed the existence of functional groups in KSC. Meanwhile, XRD spectra presented the crystallinity by diffraction peak and crystal lattice of KSC. Overall, results from FTIR and XRD analyses suggest that both kombucha SCOBY cellulose obtained from tea and pumpkin peel fermentation substrates possess similar physicochemical properties to that of commercial cellulose. In conclusion, the application of tea and pumpkin peel waste as fermentation substrates in production of kombucha SCOBY cellulose is feasible.

Trends in Venous Thromboembolism and Chemoprophylaxis Utilization in Elective Total Knee Arthroplasty From 2011 to 2020

BackgroundVenous thromboembolism (VTE) is a feared complication of joint arthroplasty, leading to recent clinical practice guidelines aimed at VTE prevention and prophylaxis. However, limited studies have examined national changes in practice regarding chemoprophylaxis and the resultant changes in VTE rates. The purpose of this study was to identify: (1) the temporal trends in thrombotic complications; and (2) changes in chemoprophylaxis utilization in patients undergoing elective total knee arthroplasty (TKA). MethodsA retrospective study was conducted using a large all-payer claims dataset. Patients who underwent osteoarthritis-indicated TKA between 2011 and 2020 were identified. Annual rates of VTE, including deep vein thrombosis and pulmonary embolism, within 90 days of TKA were determined. Utilization patterns for postoperative aspirin and anticoagulant medications were observed. Temporal trends were analyzed with linear regression and the calculation of the cumulative annual growth rate. Multivariable logistic regression was conducted to account for the effects of age and comorbidities. ResultsA total of 1,263,351 TKA patients were identified between 2011 and 2020. There were significant reductions in VTE rates (2.9% in 2011 to 1.8% in 2020), deep vein thrombosis rates (2.0% in 2011 to 1.3% in 2020), and pulmonary embolism rates (1.1% in 2011 to 0.6% in 2020). Postoperative utilization of aspirin increased from 5.9% in 2011 to 53.2% in 2020, whereas utilization of anticoagulants decreased from 94.1% in 2011 to 46.8% in 2020. Among anticoagulants, direct factor Xa inhibitors had the greatest increase in utilization (4.6 to 69.7%). The average reimbursement associated with VTE after TKA decreased from $18,061 in 2011 to $7,835 in 2020. ConclusionsThe incidence rate and economic burden of VTE after TKA have significantly declined since 2011. There has been a trend toward increased aspirin and direct oral anticoagulant utilization for postoperative chemoprophylaxis. Level of EvidenceLevel III.

Feature fusion method for pulmonary tuberculosis patient detection based on cough sound.

Since the COVID-19, cough sounds have been widely used for screening purposes. Intelligent analysis techniques have proven to be effective in detecting respiratory diseases. In 2021, there were up to 10 million TB-infected patients worldwide, with an annual growth rate of 4.5%. Most of the patients were from economically underdeveloped regions and countries. The PPD test, a common screening method in the community, has a sensitivity of as low as 77%. Although IGRA and Xpert MTB/RIF offer high specificity and sensitivity, their cost makes them less accessible. In this study, we proposed a feature fusion model-based cough sound classification method for primary TB screening in communities. Data were collected from hospitals using smart phones, including 230 cough sounds from 70 patients with TB and 226 cough sounds from 74 healthy subjects. We employed Bi-LSTM and Bi-GRU recurrent neural networks to analyze five traditional feature sets including the Mel frequency cepstrum coefficient (MFCC), zero-crossing rate (ZCR), short-time energy, root mean square, and chroma_cens. The incorporation of features extracted from the speech spectrogram by 2D convolution training into the Bi-LSTM model enhanced the classification results. With traditional futures, the best TB patient detection result was achieved with the Bi-LSTM model, with 93.99% accuracy, 93.93% specificity, and 92.39% sensitivity. When combined with a speech spectrogram, the classification results showed 96.33% accuracy, 94.99% specificity, and 98.13% sensitivity. Our findings underscore that traditional features and deep features have good complementarity when fused using Bi LSTM modelling, which outperforms existing PPD detection methods in terms of both efficiency and accuracy.

Unexpected HCHO transnational transport: influence on the temporal and spatial distribution of HCHO in Tibet from 2013 to 2021 based on satellite

Formaldehyde (HCHO) is a serious hazardous air pollutant and crucial precursor of PM2.5 and ozone compound pollution. There has been a dearth of HCHO research in Tibet where pressing need to protect the unique ecosystem. Therefore, this study aims to investigate the spatial-temporal distribution of HCHO from 2013 to 2021 and identify its influencing factors using satellite observations. Our findings reveal a noteworthy annual growth rate of 2.25% yr−1 in HCHO vertical column density (VCD) in Tibet. This rate is comparable to that in India and even surpasses levels observed in many other regions worldwide, including eastern China. Furthermore, unlike other areas, the eastern region of Tibet exhibits no discernible seasonal pattern in HCHO VCD. The anomalous variation in HCHO concentrations in Tibet can primarily be attributed to long-distance transnational transport originating from incomplete combustion in India Assam. Our research underscores the urgent need for enhanced atmospheric environmental management in Tibet.

Statistical analysis of gold production in South Africa using ARIMA, VAR and ARNN modelling techniques: Extrapolating future gold production, Resources–Reserves depletion, and Implication on South Africa's gold exploration

South African gold mining is one of the main contributors to the country's economic growth and employment creation. Assessment of future gold production is pivotal for positioning the country's supply security and contribution to the projected global demand. In this study, we modelled and forecasted South African and global gold production trends (1990–2022) using the Autoregressive Integrated Moving Average (ARIMA), Vector Autoregressive (VAR), and Autoregressive Neural Network (ARNN) techniques. The study also evaluated the impact of annual productions on the collated reserves (2008–2021) and the contribution of resource–reserve conversion in sustaining gold reserves within the South African goldfields. The ARIMA (1,1,0) model, based on root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), outperformed both ARNN (1,1) and VAR (2) methods. The forecast of the ARIMA model showed an increase in South Africa's gold production, with a compounded annual growth rate (CAGR) of ∼0.6%. The model also predicted an increase in global gold production, with CAGR of ∼2.2%. The analyses of reserves–production trends showed that most South African mining companies have been depleting their gold reserves due to production and were minimally converting resources to reserves, averaging at ∼2%/year from 2017 till present. The minimal conversion may also reflect the challenging mining conditions (such as mining depths and underground flooding) and the mining industry's socio-political dynamics. We demonstrated that, if the resource–reserve conversion factor is maintained (at ∼2%/year and above), the forecasted production may sustain the current reserves (at > 2000 t Au excluding tailings) but deplete ∼27 % of the resources to reserves by 2040. However, if the conversion factor continues to decline (to <1 %), the forecasted gold production will reduce the reserves to < 500 t Au with ∼3% of the resources converted to reserves.

Emotional labour in nursing research: A bibliometric analysis.

This study aims to conduct a comprehensive bibliometric analysis to explore the trajectory and thematic developments of emotional labour research in nursing. Utilizing descriptive and bibliometric analysis techniques. The data analysis and graphical presentation were conducted using the Bibliometrix Package in R software. The Web of Science Core Collection (WoSCC) database was searched on October 20, 2023. From 1992 to 2023, 842 authors published relevant articles, yielding 779 author keywords. There has been a general upward trend in the number of articles published over the past 30 years, with an annual growth rate of 11.71%. Keyword co-occurrence cluster analysis revealed the main focus areas of research on emotional labour antecedents and consequences, regulatory modalities, training and education, as well as research methods and application scenarios. Emotional labour significantly influences nursing staff's well-being and patient care outcomes. Effective management and education regarding emotional labour are crucial for enhancing nursing staff performance and patient care quality. Future research should focus on long-term effects, training efficacy, regulatory strategies across clinical settings, and innovative approaches to address current challenges. This study provides valuable insights into the unique trajectory and thematic developments of emotional labour research in nursing. The findings underscore the importance of addressing emotional labour in nursing practice and education to improve patient care outcomes and nursing staff well-being. Adherence to recognized bibliometric reporting methods, following relevant EQUATOR guidelines. This study is based solely on existing literature and did not involve patients or the public in its design, conduct, analysis, interpretation, or preparation.

Spatiotemporal distribution of mangrove along the Egyptian Red Sea coast and analysis of hydrological impact on growth patterns

AbstractThis study presents an in-depth spatiotemporal analysis of mangrove ecosystems along Egypt’s Red Sea coast, utilizing satellite imagery and GIS to examine changes from 2003 to 2022. We evaluate the effects of hydrological factors, specifically rainfall and runoff -presented by Stream Power Index-, on mangrove growth patterns. Results indicate a significant increase in mangrove areas, with a notable annual growth rate, despite a reduction in a specific region. This research highlights the integral role of catchment area runoff (R2 = 0.735, R = 0.857, P-value = 0.003 &lt; 0.05, CV = 70.26%), rather than direct rainfall, in mangrove expansion, contributing to the understanding of mangrove resilience and informing sustainable coastal management strategies. The study bridges a significant research gap by mapping decadal mangrove changes, offering insights into the dynamics affecting these crucial ecosystems.

Historical development, impact mechanism and future trends of nitrogen footprint in Wuxi City, China

Human activities have changed the biogeochemical cycle of nitrogen, leading to a large amount of reactive nitrogen (Nr) into the environment, aggravating a series of environmental problems, affecting human and ecosystem health. Cities are the core areas driving nitrogen cycling in terrestrial ecosystems, however, there are numerous influencing factors and their contributions are unclear. The nitrogen footprint is an important index to understand the impact of human activities on the environment, however, the calculation of urban nitrogen footprint needs a simplified and accurate system method. Here we use a nitrogen footprint calculation model at the urban system level based on system nitrogen balance, and a multi-factor extended STIRPAT (stochastic impact by regression on population, affluence, and technology) model suitable for analyzing the impact mechanism of nitrogen footprint to estimate nitrogen footprint of Wuxi City during 1990–2050. We find that: (1) from 1990 to 2020, the total nitrogen footprint of Wuxi City was in an increasing trend, but the per capita nitrogen footprint was in a decreasing trend. The per capita nitrogen footprint of 22.36 kg capita−1 in 2020 was at a lower level globally. (2) Nr discharge from fossil fuel combustion and Haber-Bosch nitrogen fixation accounted for the main proportion of nitrogen footprint. (3) Dietary choice (Ad), GDP per capita (Ag), urbanization rate (Au), population (P), and fossil energy productivity (Te) were the key factors contributing to the increase of the nitrogen footprint, which resulted in an annual increase of 1.39 %. While nitrogen footprint productivity (Tn), nitrogen use efficiency in crop farming (Tc), and nitrogen use efficiency in animal breeding (Ta) were the key inhibit factors that inhibit the increase of nitrogen footprint, and these factors slow down the annual growth rate of nitrogen footprint by 0.39 %. (4) The continuous growth of nitrogen footprint in the baseline and population growth scenarios will bring more environmental problems and greater environmental governance pressure to Wuxi City, while the sustainable scenario that includes comprehensive means such as economic adaptation and technological improvement is more in line with the requirements of high-quality development in China. Several mitigation measures are then proposed by considering Wuxi's realities from both key impact factors and potential for nitrogen footprint reduction in different scenarios, which can provide valuable policy insights to other cities, especially lakeside cities to mitigate nitrogen footprint.

The Impact of High-Standard Farmland Construction Policies on the Carbon Emissions from Agricultural Land Use (CEALU)

Agricultural activities are the second largest source of greenhouse gas emissions, and carbon emissions from agricultural land use (CEALU) have become a hot issue across the world. Although there are some studies on the impact of high-standard farmland construction policies on carbon emissions, they focus on quantitative analysis and do not give sufficient consideration to the relationship between HSFC and CEALU. Therefore, in this study, by relying on provincial panel data of China for the period 2005–2017, the effect of the high-standard basic farmland construction policy on carbon emissions from agricultural land use per unit area and its regional differences were quantitatively analyzed using the difference-in-difference (DID) model. The results showed that: (1) China’s CEALU per unit area presented a fluctuating upward change, but the growth rate slowed down during the period 2005–2017, from 392.58 kg/ha to 457.72 kg/ha, with an average annual growth rate of 1.31%; (2) the high-standard farmland construction (HSFC) policy led a significant carbon emission reduction effect in agricultural land use and reduced the CEALU per unit area by 10.80% on average. With the promotion of this policy, its carbon emission reduction effect in agricultural land use presented an overall increasing change; (3) the carbon emission reduction effect of the high-standard farmland construction policy in agricultural land use was significant in central China, but non-significant in eastern China and western China.

Spatiotemporal dynamics of urban sprawl in China from 2000 to 2020

ABSTRACT Accurately and timely quantifying the dynamics of urban sprawl is essential for improving land use efficiency and land use planning. However, existing research mainly focused on the sprawl of a single city or urban agglomerations in China, while national scale studies mainly used short-term remote sensing data to quantify urban sprawl. Therefore, we still lack a long term and most up-to-date understanding of urban sprawl in China, especially in different regions, cities of different sizes. Here, we quantified the spatiotemporal dynamics of urban sprawl using urban sprawl index (USI) based on the latest population census, and analyzed its driving force in China during 2000 ~ 2020 using the optimal parameters-based geographical detector. The results showed that in the past two decades, Chinese cities were still experiencing urban sprawl, with an average USI of 3.04, indicating that the average annual growth rate of urban lands was 3.04% higher than that of the urban population. Overall, the sprawl showed a slowdown, with the USI dropping from 3.55 in 2000 ~ 2010 to 2.53 in 2010 ~ 2020. Among regions, urban sprawl was more severe in the western region, where the USI was 5.33 during 2000 ~ 2020 and 89.3% of the cities exceeded the national average sprawl speed. Recently, the driving force of transportation on urban sprawl substantially increased. In the future, the Territorial Spatial Planning should pay attention to confining excessive sprawl of small- and medium-sized cities in the western region of China.

Effects of Urban Growth and Urbanization on the Social Environment: Case Study Old and Modern Cities of Yemen

Aim: This research was designed to study the effects of urban growth and urbanization on the social environment (Study of the state of growth and social changes in the old and modern cities of Yemen an example). Background: Yemenis have a rich history of urban centers, which have played a crucial role in trade, crafts, industries, and science. These cities have become distinct areas of cultural development, economic polarization, and cultural radiation. They are considered crucibles for social culturalintegration, nurseries for political growth, and areas for the development of national consciousness. The history of Yemen's cities and urban centers demonstrates the close link between trade, delivery routes, political governance centers, and city growth and development. Some Yemeni historical cities have played a vital role before Islam as political capitals, educators, and seaports. Cities have emerged as a result of the desire to coexist and achieve stability, reflecting spiritual, material, social, and political conditions. The growth of cities and architecture is a reflection of these changes. Methodology: The physical changes in the Republic of Yemen and the identification of the city of Aden were studied by reviewing the studies that monitored these changes and their social, economic and population effects. The study relied on secondary data in the first place. Conclusion: Yemen's population growth rate in 2004 was low at 3.01%, but it remains high due to economic and social developments and changes demographic factors such as fertility, mortality, and migration the growth rate was decreased at 2.20%. The 2004 General Population and Housing Census revealed that the resident population is spread across various governorates, with Ta'izz, Hodeidah, and Ibb having the highest proportions. The General Census of Population and Establishments revealed changes in the relative weight of the provincial population between the 1994 and 2004 censuses, with some governorates experiencing an increase in population relative to the population, while others experienced a decrease. The annual growth rate of the resident population was 3.0%, and the proportion of the young age group increased from 46.2% in 1994 to 51.5% in 2004. The gender ratio in Yemen is 104, with some governorates having a higher proportion of species due to urbanization (male than more than female), employment opportunities, or male labor migration. The Central Statistical Agency predicts that population growth will remain high over the next 20 years, with a natural increase rate of 3.01%. The proportion of married people in the population is higher for both sexes, possibly due to increased living costs and lack of adequate housing.

Glioblastoma: a comprehensive approach combining bibliometric analysis, Latent Dirichlet Allocation, and HJ-Biplot : Glioblastoma insights and trends: a 49-year bibliometric analysis.

Glioblastoma is a common and aggressive malignant central nervous system tumor in adults. This study aims to evaluate and analyze the scientific results, collaboration countries, main research topics, and topics over time reported about glioblastoma. A bibliometric analysis of glioblastoma publications was performed mainly using R and Multbiplot software for author, journal, and resume. Associated statistic methods Latent Dirichlet Allocation (LDA) and HJ-Biplot. Inclusion criteria were research articles from the PubMed database published in English between 1973 and December 2022. A total of 64,823 documents with an annual growth rate of 8.27% indicates a consistent increase in research output over time. The results for the number of citations and significant publications showed Cancer Res, J Neuro-Oncol, and Neuro-Oncology are the most influential journals in the field of glioblastoma. The countries that concentrated research were the tumor United States, China, Germany, and Italy. Finally, there has been a marked growth in studies on prognosis and patient survival, therapies, and treatments for glioblastoma. These findings reinforce the need for increased global resources to address glioblastoma, particularly in underdeveloped countries. Glioblastoma research's exponential growth reflects sustained interest in early diagnosis and patient survival.

Evaluation of resource and environmental carrying capacity in Xiong’an New Area

From four dimensions of resource, environment, ecology (green ecology) and social economy, correlation analysis method and principal component analysis method of SPSS are used to screen evaluation indexes to design a scientific and reasonable evaluation indexes system of resource and environmental carrying capacity in Xiong’an New Area in line with regional characteristics. Based on fuzzy comprehensive evaluation method, resource and environmental carrying capacity of the New Area are evaluated. The results show that: the resource and environmental carrying capacity of the New Area from 2014 to 2018 are 0.3229, 0.3556, 0.3521, 0.3859 and 0.4445 respectively, with an average annual growth rate of 8.32% and a steady growth trend. Then, some countermeasures to improve resource and environmental carrying capacity of the New Area are presented from three aspects of development and utilization of land resource, development and utilization of water resource and protection and utilization of water environment.

Social, economic, and demographic factors drive the emergence of Hinglish code-mixing on social media

The advent of globalization and adaptation to multiple cultures has emanated a fusion of Hindi and English, casually known as Hinglish. The phenomenon of mixing multiple languages (such as Hindi and English) within a single utterance is often called code-mixing. Lately, code-mixed Hinglish has emerged as a dominant conversational language for Hindi-speaking citizens both online (on social media platforms) and offline. Although previous studies investigated such linguistic traits of Hinglish over the past few years, some pertinent questions still need to be answered: How did Hinglish evolve? And, what are the factors behind the evolution of Hinglish? Does the fusion of English impact all Hindi words similarly? To this end, we explore the empirical and statistical shreds of evidence behind the rise of Hinglish on social media such as Twitter. We show that adopting Hinglish depends on several socio-economic and demographic factors. We further formulate dynamic models to explore the socio-economic factors driving the growth of Hinglish, derive the future growth of Hinglish in the upcoming years, and estimate the propensity of users to change their linguistic preferences. Our study highlights that the Hinglish population has evolved steadily between 2014 and 2022, with an annualized growth rate of 1.2%, and the usage of Hinglish on Twitter has increased annually by 2%. Further, we find that the impact of Hinglish evolution is not uniform across different word groups and affects the contextual meaning of different words differently. Although our findings are specific to the Indian Hinglish community, our study can be generalized to understand the evolution and dynamics of other code-mixed languages, such as Spanish-English or Chinese-English.

Trends in Medicare Reimbursement for Common Pediatric Orthopedic Procedures: From 2000 to 2022.

Objective We aimed to evaluate trends in government monetary reimbursement (Medicare) for 10 of the most commonly performed pediatric orthopedic procedures from 2000 to 2020. Methods Utilizing the Centers for Medicare and Medicaid Services website, we collected data for 10 of the most commonly performed pediatric orthopedic surgical procedures and their variations. The reimbursement data for each procedure was taken from the Current Procedural Terminology (CPT) code, which was collected from the Physician Fee Schedule Look-Up Tool from the Centers for Medicare and Medicaid Services (Baltimore County, MD). The reimbursement values were adjusted for inflation to the 2022 US dollar (USD) using the changes to the Consumer Price Index. The compound annual growth rates (CAGRs) and total percentage changes in reimbursement were calculated for all the procedures and put into relative value units. Results Reimbursement for 20 of the 22 total procedures decreased by 32.65% from 2000 to 2022 after adjusting for inflation. Achilles tenotomy with local anesthesia saw the greatest decrease (-54.38%), whereas the procedure revision of spinal fusion saw the highest increase (26.00%) in mean adjusted reimbursement during this study period. Adjusted reimbursement decreased by an average of 2.08% on a yearly basis. Conclusion This study is the first to take an in-depth view and evaluate trends in procedural Medicare reimbursement for pediatric orthopedic surgery. When adjusted for inflation, Medicare reimbursement for 20 of 22 included procedures has steadily decreased from 2000 to 2022. There needs to be an increased awareness and consideration of these trends as they will be important for policymakers, hospitals, and surgeons to ensure continued access to meaningful surgical pediatric orthopedic care in the United States.

Unraveling the dynamics of atmospheric methane: the impact of anthropogenic and natural emissions

The reduction in methane concentration is crucial for achieving the goals of the Paris agreement. However, its annual growth rate is unstable, and understanding the reasons for changes in methane growth is essential for climate policy-making. Currently, there is considerable uncertainty regarding its attribution. Here, we utilize multi-source data and optimal fingerprinting methods to detect the contributions of several key drivers to the methane trend and interannual variability. We find that the methane growth trend is primarily influenced by anthropogenic emissions, while interannual variability is predominantly determined by wetland and biomass burning emissions. This result underscores the central role of anthropogenic emissions in methane dynamics, providing confidence in the effectiveness of human efforts to control methane atmospheric concentrations through emission reductions. It also helps alleviate concerns about the recent surge in atmospheric methane concentration, as it may be a short-term peak caused by increased wetland emissions rather than a long-term change.

Towards food security: Exploring the spatio-temporal dynamics of soybean in India

India is the world’s largest edible oil importer, and soybean oil accounts for a major portion of those imports, with implications for the Indian economy. Despite being the 4th largest globally in terms of harvested soybean area and 5th largest in terms of production, India is still heavily dependent on imports to meet the vegetable oil requirement for its population. It is therefore imperative to understand the dynamics and trends in India’s soybean production to help the country achieve self-sufficiency in edible oils. This study provides the first spatially explicit analysis of soybean in India, using long-term spatial and temporal statistics at national and subnational levels, using spatial and temporal statistical analysis models to examine the historical trends and its future prospects. Our analysis details the overall soybean expansion across the country and the increase in production but we also note that the annual growth rate has declined in each consecutive decade even though the area continues to expand. The average national yield has been stagnant at around 1 T/Ha but for some of the low-producing districts, a higher yield of more than 3 T/ha is reported. For most major producing districts, soybean yields are below 1.5 T/Ha. The state of Madhya Pradesh which was the major soybean producer is now matched by the state of Maharashtra in terms of production, however, Madhya Pradesh still has the largest area under soybean. We analyzed soybean hotspot expansion in India and found that the mean center of the soybean area and production has shifted approximately 93 km towards the south and 24 km to the west as the crop is rapidly being adopted in the southern and western parts of India expanding the hotspot in these parts. District-level analysis showed that the total number of districts constituting hotspots of soybean cultivation in India has increased from 29 to 42 in three decades. Furthermore, analysis of soybean oil and meal consumption with respect to the national population, import, export, domestic production, GDP per capita, and price of soybean oil and meal suggests that soybean oil and meal are highly correlated with GDP per capita and population, indicating that consumption of soybean oil and meal is likely to increase as GDP per capita increases, and future demand is expected to rise with the anticipated growth in the Indian population. Increased soybean production can play a significant role in increasing national food security for India and reducing dependence on foreign oil imports and also help the economy with soy meal exports. Understanding the spatiotemporal variability in area and yield will help target interventions to increase production. Given the overall low yields with high variability in production, particularly in recent years primarily due to successive extreme rains and droughts in major producing districts and the overall need to increase production to meet the country’s demand, there is a pressing need for government policies and research aimed at narrowing the yield gap and developing soybean varieties that are more productive and resilient to climate change.

An integrated assessment of erosion drivers facilitating gully expansion rates—A near century multi‐temporal analysis from South Africa

AbstractRural areas in the Eastern Cape Province of South Africa are severely affected by gully erosion, yet little is known about the rates at which these features are expanding. This study explores the areal extent, physical mechanisms, rates, and drivers of gully expansion with the aim of investigating how erosion rates fluctuate in response to temporal variations of drivers over the last century. Investigations involved the creation of an erosion inventory geo‐database, the identification of area‐specific physical expansion mechanisms, an assessment of static and dynamic drivers, and a multi‐temporal study of 25 gullies in the Mthatha area. Results show gully erosion affects 2.3% of the study area, with gullies exhibiting an average annual areal increase of 2.08%, a sidewall retreat rate of 0.2 m/y, and a headcut retreat of 1.03 m/y over an 82‐year period between 1938 and 2020. A multi‐temporal case study of the Ngwevana Gully showed average annual areal growth rates ranging from 3.9% between 1938 and 1948 to 0.7% between 2017 and 2020. Findings indicate that although gullies consistently expand their areal footprint, they do so at fluctuating rates. An assessment of erosion drivers reveals that temporal promotion or suppression of these erosion rates occurs in response to the complex and dynamic interactions of both natural mechanisms and anthropogenic activities. In Mthatha, the periods of increased rates of erosion are linked to large‐scale flooding events during drier climate cycles, which were further exacerbated by invasive dryland agricultural practices, inappropriate land use, haphazard infrastructure development, and rapid population increases facilitated by past Apartheid settlement laws.