Mitigating urban heat island and enhancing indoor thermal comfort using terrace garden

The United Nations advocates for sustainable urban planning and design, emphasizing green infrastructure initiatives to mitigate urban heat island effects and enhance the resilience and livability of cities globally. To address urban heat challenges, a study was conducted in Chennai, India, from April to June 2023. The study focused on assessing temperature dynamics on a building's terrace by comparing a well-maintained garden area with an exposed region. Temperature and humidity sensors were deployed in both the garden and exposed areas of the terrace, as well as within rooms beneath it, to monitor hourly temperature fluctuations. The findings indicate a significant reduction in internal room temperatures in areas with rooftop gardens, ranging from 4 to 11 °C, depending on the time of year and sun's position, compared to rooms with fully exposed roof configurations. Additionally, simulation studies were performed to validate these findings, suggesting that optimizing the distribution of soil beds and plant density across the roof could yield an additional temperature reduction of 3-4 °C, resulting in an overall difference of up to 14-15 °C. The study highlights the efficacy of rooftop gardens in providing cooling effects during daylight hours and maintaining temperature parity post-sunset. Through analysis of sensor data, the research elucidates the intricate relationship between green infrastructure and thermal comfort, offering insights for energy-efficient building design and resilient urban planning. The findings underscore the potential of rooftop gardens in fostering a more comfortable, energy-efficient, and sustainable urban living environment.

Increasing obsidian diversity during the Chalcolithic Period at Yeghegis-1 Rockshelter (Armenia) reveals shifts in land use and social networks

The newly excavated rockshelter of Yeghegis-1 in Armenia reflects an occupation of five centuries, as attested by radiocarbon dates from ∼ 4100 to 4000 cal BCE in the lowest layer to ∼ 3600-3500 cal BCE at the top. It is a partially collapsed cave in which pastoralists, we hypothesize, wintered with their herds. The stone tool assemblage is predominantly obsidian (92.1%), despite the shelter being > 60 km on foot from the nearest sources. We use obsidian sourcing to investigate two purported trends in the Southern Caucasus during the Chalcolithic Period: (1) occupation of more varied high-altitude environments and (2) more expansive social networks. Our data show both trends were dynamic phenomena. There was a greater balance in use of the nearest pasturelands over time, perhaps linked to risk management and/or resource sustainability. During later occupations, artifacts from distant sources reveal more extensive connections. This increase in connectivity likely played a central role in the shifts in societal complexity that gave rise to widely shared material culture throughout the Armenian Highlands around the start of the Early Bronze Age. In such a model, greater social connectivity becomes a key mechanism for, rather than a product of, the spread of cultural and/or technological innovations.

RASMI: Global ranges of building material intensities differentiated by region, structure, and function

The construction materials used in buildings have large and growing implications for global material flows and emissions. Material Intensity (MI) is a metric that measures the mass of construction materials per unit of a building's floor area. MIs are used to model buildings' materials and assess their resource use and environmental performance, critical to global climate commitments. However, MI data availability and quality are inconsistent, incomparable, and limited, especially for regions in the Global South. To address these challenges, we present the Regional Assessment of buildings' Material Intensities (RASMI), a new dataset and accompanying method of comprehensive and consistent representative MI value ranges that embody the variability inherent in buildings. RASMI consists of 3072 MI ranges for 8 construction materials in 12 building structure and function types across 32 regions covering the entire world. The dataset is reproducible, traceable, and updatable, using synthetic data when required. It can be used for estimating historical and future material flows and emissions, assessing demolition waste and at-risk stocks, and evaluating urban mining potentials.

Evaluating the potential and eligibility of conservation agriculture practices for carbon credits

Carbon credits, a voluntary market mechanism to reduce greenhouse gas (GHG) emissions, can incentivize climate action. We evaluate the potential and eligibility of Conservation Agriculture (CA) practices for carbon credit generation in India under Verra's VM0042 methodology. Using farmer surveys and remote sensing data, we assess the eligibility based on the following conditions: Additionality Condition (GHG emission reductions to exceed legal requirements and the weighted mean adoption rate to be < 20% of area in the baseline), Yield Penalty Condition (no > 5% decrease in crop yields), and Quantitative Adjustment Condition (reduction in chemical fertilizer use by > 5%). Our analysis shows that CA has the potential to increase farmers' carbon credit earnings by USD 18/ha and USD 30/ha in Bihar and Punjab, respectively. Punjab's ban on crop residue burning and the fact that > 20% of the area unburned limits the full economic realization of CA through carbon markets, decreasing potential income to USD 16/ha. A 60% increase in carbon prices from the current norm (USD 25) is required to encourage wider adoption of CA. Zero tillage of wheat in both Punjab and Bihar and reduction of nitrogen fertilizer overuse in Punjab fulfil all the conditions and are eligible for carbon farming projects.

Exponential growth of private coastal infrastructure influenced by geography and race in South Carolina, USA

Homeowners in coastal environments often augment their access to estuarine ecosystems by building private docks on their personal property. Despite the commonality of docks, particularly in the Southeastern United States, few works have investigated their historical development, their distribution across the landscape, or the environmental justice dimensions of this distribution. In this study, we used historic aerial photography to track the abundance and size of docks across six South Carolina counties from the 1950s to 2016. Across our roughly 60-year study period, dock abundance grew by two orders of magnitude, mean length of newly constructed docks doubled, and the cumulative length of docks ballooned from 34 to 560 km. Additionally, we drew on census data interpolated into consistent 2010 tract boundaries to analyze the racial and economic distribution of docks in 1994, 1999, 2011, and 2016. Racial composition, measured as the percentage of a tract's population that was White, positively correlated with dock abundance in each year. Median household income and dock abundance were only correlated in 2011. Taken together, these metrics indicate the growing desire for direct estuary access, however, that access does not appear to be equally spread across racial groups. Because docks enhance estuarine access and demarcate private property, our study provides longitudinal insights into environmental justice concerns related to disparate private property ownership. We found a persistent correlation between the racial characteristics of an area and dock abundance, strongly indicating that White South Carolinians have had disproportionately greater private water access for the past two decades.

A study on why foreign-born East Asians but not US-born East Asians are underrepresented in leadership attainment in the U.S

A recent study investigated the impact of culture of Asian groups on leadership attainment in the U.S. It revealed that East Asians (EAs) are less likely than South Asians (SAs) and white people (WP) to attain leadership positions, and SAs may even surpass WP in leadership attainment. The study explained that the underrepresentation of EAs in leadership positions in the U.S. (the so called bamboo ceiling) is partly because EAs communicate less assertively. Specifically, EA cultures value collectivism (e.g., humility and harmony), which are at odds with western cultures that value individualism (e.g., extraversion and assertiveness), whereas SA cultures are congruent with western cultures. However, the study did not distinguish the different impact of home culture (i.e., EA cultures) and host culture (i.e., western cultures) on US-born EAs versus foreign-born EAs. We argue that for US-born EAs (i.e., second generation EAs), host culture plays a more important role than home culture in their growth and they may not be underrepresented in leadership attainment compared to WP. The bamboo ceiling effect is mostly demonstrated among foreign-born EAs (i.e., first generation EAs) who are shaped mainly under the home culture. We support the argument by conducting analysis on one of the datasets in the original study and a new dataset from Fortune's 40-under-40 list. Our study suggests that when studying the underrepresentation of leadership attainment for EAs, US-born EAs and foreign-born EAs should not be aggregated in one category. Considering the ethnic EA group, the bamboo ceiling phenomenon may exist mainly among foreign-born EAs because US-born EAs, with a median age of 21.3, are much younger than the general American population, who may not be experienced enough to be considered for leadership positions in established large companies.

Incidence of coronary heart disease among remote workers: a nationwide web-based cohort study

Coronary heart disease (CHD) risk is influenced by socioeconomic status-related parameters, particularly occupation. We investigated occupational gaps in CHD risk and how the introduction of remote work moderated the observed occupational differences in CHD risk during the coronavirus disease 2019 pandemic in Japan. Data from a web-based, nationwide cohort study, comprising 17,640 workers (aged 20-65 years) with baseline data from December 2020, were analyzed. Participants were grouped by occupation as upper-level nonmanual workers (managers/professionals) and others (reference group). The primary outcome was CHD (angina pectoris/myocardial infarction) onset retrospectively confirmed at the 1-year follow-up survey. Upper-level nonmanual workers exhibited a higher CHD incidence than others (2.3% vs. 1.7%). This association was pronounced in the younger (20-49 years) population, with a significant CHD risk (adjusted risk ratio = 1.88). Upper-level nonmanual workers exhibited nearly 15% higher remote work prevalence, with a significant remote work-related CHD risk (adjusted risk ratio = 1.92). The mediating effects of remote work explained an overall disparity of 32% among the younger population. Occupational gaps in CHD incidence in Japan differ from those in Western countries, where upper-level nonmanual workers have lower cardiovascular risk. In Japan, remote work can mediate CHD risk in the younger population of upper-level nonmanual workers.

The effect of a political crisis on performance of community forests and protected areas in Madagascar

Understanding the effectiveness of conservation interventions during times of political instability is important given how much of the world's biodiversity is concentrated in politically fragile nations. Here, we investigate the effect of a political crisis on the relative performance of community managed forests versus protected areas in terms of reducing deforestation in Madagascar, a biodiversity hotspot. We use remotely sensed data and statistical matching within an event study design to isolate the effect of the crisis and post-crisis period on performance. Annual rates of deforestation accelerated at the end of the crisis and were higher in community forests than in protected areas. After controlling for differences in location and other confounding variables, we find no difference in performance during the crisis, but community-managed forests performed worse in post-crisis years. These findings suggest that, as a political crisis subsides and deforestation pressures intensify, community-based conservation may be less resilient than state protection.

A study of the impact of risk perception on the pro-environmental behaviour of herders in the Sanjiangyuan region

This study aims to study the pro-environmental behaviour of herders in the Sanjiangyuan region, a significant ecological security barrier. This paper selected 212 herding households in the Sanjiangyuan area as research subjects by random sampling method. By establishing a multivariate ordered logistics model to study the impact of risk perception on herding households' pro-environmental behaviour and introducing capital endowment as a moderating variable to analyse the moderating effect of capital endowment on the relationship of herding households' risk perception-pro-environmental behaviour. The study results show that herders's risk perception significantly affects their pro-environmental behaviour, in which environmental risk perception, economic risk perception and disease risk perception positively affect their pro-environmental behaviour. Capital endowment has a moderating role in the relationship between risk perception and the pro-environmental behaviour of herding households. Accordingly, this paper proposes to strengthen publicity and education, encourage herders to join cooperatives, and improve the ability of risk perception and other countermeasures.

A lower connection to nature is related to lower mental health benefits from nature contact

Increasing evidence demonstrates the psychological benefits of nature contact. However, the evidence is often established at the population level, and the individual differences in the psychological benefits gained from nature are considered negligible variations. In this study, we performed a cross-sectional online survey in Brisbane and Sydney, Australia, from April 15th and May 15th, 2021 around one year after the first covid-19 pandemic lockdowns. The results show that individuals with a stronger connection to nature are linked with a lower level of stress and anxiety with increased frequency in public greenspace visits, while such an association is less clear for individuals with a weaker connection to nature. We also find that, through the answer to an open-ended question, individuals with a lower connection to nature tend to mention nature-related words less as the reason for visiting greenspace. This indicates that a person's connection to nature is linked with how they interact with nature and thus might determine whether and how much psychological benefit a person gains from experiencing nature.

Optimization of Chinese land spatial pattern in the transformation process of resource-based cities: a case study in Tongling City, China

Optimizing the spatial layout of the national territory is crucial for realizing the transformation and development of resource-oriented cities in the context of high-quality development in the new period. This paper takes Tongling City as a case study, based on the analysis of the historical development foundation, then uses the SD-FLUS comprehensive model to carry out a systematic analysis of the transformation in five dimensions of economy, society, population, science and technology, resources and environment, and discusses the optimization of spatial pattern under the contextual simulation. The conclusions are as follows: ① The hierarchical framework of "system-indicator-element" is not only internally interconnected, but also inextricably linked with the relationship between the various categories of the land use system. ② Decrease of cropland, forest, water, grassland, and barren decreases from the economic development, social progress, and comprehensive development, and there is a small increase in the area under the scenario of resource and environmental protection, and the direction of the change of the impervious is in the opposite direction. ③ Cultivated land is retained in situ and concentrated to a small extent, forested land is reduced to a small extent while the status quo is maintained, and the Yangtze River water system will be retained and protected to a large extent, but part of the waters of Zongyang County will give way to the expansion of construction land under the development objectives of the new county. Building land will be expanded and extended to the northeast in the original site area, while the southwest corner of the original county center will be expanded to some extent in Zongyang County to promote the county's economic development.

Assessing groundwater denitrification spatially is the key to targeted agricultural nitrogen regulation

Globally, food production for an ever-growing population is a well-known threat to the environment due to losses of excess reactive nitrogen (N) from agriculture. Since the 1980s, many countries of the Global North, such as Denmark, have successfully combatted N pollution in the aquatic environment by regulation and introduction of national agricultural one-size-fits-all mitigation measures. Despite this success, further reduction of the N load is required to meet the EU water directives demands, and implementation of additional targeted N regulation of agriculture has scientifically and politically been found to be a way forward. In this paper, we present a comprehensive concept to make future targeted N regulation successful environmentally and economically. The concept focus is on how and where to establish detailed maps of the groundwater denitrification potential (N retention) in areas, such as Denmark, covered by Quaternary deposits. Quaternary deposits are abundant in many parts of the world, and often feature very complex geological and geochemical architectures. We show that this subsurface complexity results in large local differences in groundwater N retention. Prioritization of the most complex areas for implementation of the new concept can be a cost-efficient way to achieve lower N impact on the aquatic environment.

Validity evidence for the coping strategy indicator-short version (CSI-S) among psychology students

The abbreviated measurement of coping strategies is useful for monitoring and identifying the effects of stress. The Coping strategy indicator-Short version (CSI-S, including the dimensions of seeking support, problem solving and avoidance strategies) is a new adaptation of the full version of this indicator, and additional evidence of its validity is needed. Psychology students (n = 125) from a public university in Lima, Peru, were recruited to help provide such evidence of validity in terms of internal structure, reliability and associations with other variables (perceived stress and general efficacy in cope with difficulties), which were evaluated using nonparametric item response theory procedures. Support-seeking and problem-solving items from the Mokken scale and the avoidance scale exhibited limitations. The correlations between the scales were moderate or low and exhibited theoretical consistency, and the relationship with perceived stress highlighted the predictive capacity of avoidance and problem-solving strategies. In general, the CSI-S exhibits suitable psychometric properties; however, the avoidance score requires further examination or reconstruction of its items.

Development of a composite drought indicator for operational drought monitoring in the MENA region

This paper presents the composite drought indicator (CDI) that Jordanian, Lebanese, Moroccan, and Tunisian government agencies now produce monthly to support operational drought management decision making, and it describes their iterative co-development processes. The CDI is primarily intended to monitor agricultural and ecological drought on a seasonal time scale. It uses remote sensing and modelled data inputs, and it reflects anomalies in precipitation, vegetation, soil moisture, and evapotranspiration. Following quantitative and qualitative validation assessments, engagements with policymakers, and consideration of agencies' technical and institutional capabilities and constraints, we made changes to CDI input data, modelling procedures, and integration to tailor the system for each national context. We summarize validation results, drought modelling challenges and how we overcame them through CDI improvements, and we describe the monthly CDI production process and outputs. Finally, we synthesize procedural and technical aspects of CDI development and reflect on the constraints we faced as well as trade-offs made to optimize the CDI for operational monitoring to support policy decision-making-including aspects of salience, credibility, and legitimacy-within each national context.

Fine-grained urban blue-green-gray landscape dataset for 36 Chinese cities based on deep learning network

Detailed and accurate urban landscape mapping, especially for urban blue-green-gray (UBGG) continuum, is the fundamental first step to understanding human-nature coupled urban systems. Nevertheless, the intricate spatial heterogeneity of urban landscapes within cities and across urban agglomerations presents challenges for large-scale and fine-grained mapping. In this study, we generated a 3 m high-resolution UBGG landscape dataset (UBGG-3m) for 36 Chinese metropolises using a transferable multi-scale high-resolution convolutional neural network and 336 Planet images. To train the network for generalization, we also created a large-volume UBGG landscape sample dataset (UBGGset) covering 2,272 km2 of urban landscape samples at 3 m resolution. The classification results for five cities across diverse geographic regions substantiate the superior accuracy of UBGG-3m in both visual interpretation and quantitative evaluation (with an overall accuracy of 91.2% and FWIoU of 83.9%). Comparative analyses with existing datasets underscore the UBGG-3m's great capability to depict urban landscape heterogeneity, providing a wealth of new data and valuable insights into the complex and dynamic urban environments in Chinese metropolises.

Factors affecting the protection of data rights in sports events: a configurational analysis

The development of algorithms and the spread of digital infrastructure have contributed significantly to the productivity of the digital economy. Data has come to be known as the "oil of the digital economy". At the same time, data has begun to participate more deeply in the production activities of the global sports industry chain, and the international discussion on how to protect the rights of sports event data has been increasing. Based on the configurational theory and fuzzy-set qualitative comparative analysis, this study discusses the factors affecting the protection of sports event data rights. The study found three configuration paths for achieving high enterprise data protection effectiveness and two for achieving low enterprise data protection effectiveness. The results of this study provide theoretical support for governments to address the issue of sports event data rights. They will also facilitate the safe use of data in sports, promote the global sports industry and humanitarian action development, and contribute to international sustainable development.

Pro-environmental behavior regarding single-use plastics reduction in urban-rural communities of Thailand: Implication for public policy

The study investigates residents' behavior towards reducing the use of single-use plastic (SUP), specifically in the context of food packaging. The widespread view holds that pro-environmental behavior (PB) results from a person's moral and rational deliberations. In reducing single-use plastic (SUP) consumption and waste, the relative roles of rationality and morality models in validating PB among rural and urban residents are not yet clear. In this empirical study, we compared the relative efficacy of two models for explaining people's SUP reduction behavior: the theory of planned behavior (TPB; rationality) and the value belief norm (VBN; morality). We investigated Thailand's rural (Sichang Island) and metropolitan (Nonthaburi city) areas. As a result, we surveyed people living on Sichang Island (n = 255) and in Nonthaburi city (n = 310). We employed structural equation modeling (SEM) for data analysis in this study. Findings showed that while morality better justified all the study participants' SUP reduction behavior, rationality underpinned behaviors of rural residents, while morality better explained the actions of city residents. We discussed future theoretical development and a policy roadmap based on these findings.

High spatiotemporal-resolution mapping for a seasonal erosion flooding inundation using time-series Landsat and MODIS images

Seasonal erosion flooding events present a significant challenge for effective disaster monitoring and land degradation studies. This research addresses this challenge by harnessing the combined capabilities of time-series Landsat and MODIS images to achieve high spatiotemporal-resolution mapping of flooding during such events. The study underscores the critical importance of precise flood monitoring for disaster mitigation and informed land management. To overcome the limitations posed by the trade-off between spatial and temporal resolution in current satellite sensors, we emplyedand theflexible spatiotemporal data fusion (FSDAF) methods to produce synthetic flood images with enhanced spatiotemporal resolutions for mapping by using MODIS and Landsat data from August 29 to September 3, 2016. A comparison was made between flood maps from several post-disaster forecasts based on ground-obtained time-series images of the Tumen River flood in China. According to the FSDAF approach, the input Landsat image of March 25, 2016, and the fused results had a root mean square error (RMSE) of 0.0301, average difference of 0.001, r of 0.941, and structure similarity indexof 0.939, indicating that temporal variation data had been effectively incorporated into a forecast on August 16, 2016. Results also indicated that the FSDAF forecast values are lower than those from the actual Landsat image. The results of the study also showed that the generated images could be effectively used for flood mapping. By using our newly developed simulation model, we were able to produce a comprehensive map of the inundated areas during the event from August 29 to September 3, 2016. This shows that FSDAF holds great potential for flood prediction and study and has the potential to benefit further disaster-related land degradation by combining multi-source images to provide high temporal and spatial resolution remote sensing information.

Effects of landscape pattern on land surface temperature in Nanchang, China

The composition and configuration of landscapes are critical important to design effective approaches to mitigate urban thermal environment in the urbanization process. In this research, land use maps and land surface temperature (LST) retrieval were derived in Nanchang city of central China based on product datasets and the thermal infrared band of Landsat. The results showed that the thermal environment of Nanchang had become worse over the past two decades, that is, the proportion of area of the extremely low temperature zone (ELTZ) decreased from 4.39 to 0.77% from 2001 to 2020, and that of medium temperature zone (MTZ) reduced by 20%, whereas those of the high temperature zone (HTZ) and the extremely high temperature zone (EHTZ) increased sharply after 2001, and by 2020, the area ratio increased by 11% and 7.16%, respectively. The agricultural land (AL) area decreased from 68.44 to 49.69%, was gradually replaced by construction land (CL). The CL occupied the largest proportion in EHTZ, HTZ and slight high temperature zone (SHTZ); water landscape (WL) and green land (GL) occupied the largest proportion in ELTZ, low temperature zone (LTZ); and AL occupied the largest proportion in SHTZ, MTZ, and slight low temperature zone (SLTZ). Landscape configuration also obviously impacted on LST. The model fitting was well (R = 0.87) between land use area and LST by multiple regression analysis. The significant correlation between LST and six landscape pattern indices of CL (p < 0.01) indicated that the larger percent (PLANT, R = 0.78) and the more concentrate (LPI, R = 0.73) of CL implied the higher LST, while the more fragment (NP, R = - 0.45), dispersed and complex shape (R = - 0.35) were benefit to relieve LST. Contrastively, the larger percent and the more concentrated and complex shape distribution of AL, GL and WL, the lower LST (p < 0.01). In addition, LST had closely correlation with landscape level indices such as aggregation degree (AI, R = 0.44) and diversity (SHDI, R = - 0.60) (p < 0.01).

Development of a greenhouse gas - air pollution interactions and synergies model for Korea (GAINS-Korea)

This study aimed to create Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS)-Korea, an integrated model for evaluating climate and air quality policies in Korea, modeled after the international GAINS model. GAINS-Korea incorporates specific Korean data and enhances granularity for enabling local government-level analysis. The model includes source-receptor matrices used to simulate pollutant dispersion in Korea, generated through CAMx air quality modeling. GAINS-Korea's performance was evaluated by examining different scenarios for South Korea. The business as usual scenario projected emissions from 2010 to 2030, while the air quality scenario included policies to reduce air pollutants in line with air quality and greenhouse gas control plans. The maximum feasible reduction scenario incorporated more aggressive reduction technologies along with air quality measures. The developed model enabled the assessment of emission reduction effects by both greenhouse gas and air pollutant emission reduction policies across 17 local governments in Korea, including changes in PM2.5 (particulate matter less than 2.5 μm) concentration and associated benefits, such as reduced premature deaths. The model also provides a range of visualization tools for comparative analysis among different scenarios, making it a valuable resource for policy planning and evaluation, and supporting decision-making processes.

Assessing the effects of pandemic risk on cooperation and social norms using a before-after Covid-19 comparison in two long-term experiments

How does threat from disease shape our cooperative actions and the social norms that guide such behaviour? To study these questions, we draw on a collective-risk social dilemma experiment that we ran before the emergence of the Covid-19 pandemic (Wave 1, 2018) and compare this to its exact replication, sampling from the same population, that we conducted during the first wave of the pandemic (Wave 2, 2020). Tightness-looseness theory predicts and evidence generally supports that both cooperation and accompanying social norms should increase, yet, we mostly did not find this. Contributions, the probability of reaching the threshold (cooperation), and the contents of the social norm (how much people should contribute) remained similar across the waves, although the strength of these social norms were slightly greater in Wave 2. We also study whether the results from Wave 1 that should not be affected by the pandemic-the relationship between social norms and cooperation and specific behavioural types-replicate in Wave 2 and find that these results generally hold. Overall, our work demonstrates that social norms are important drivers of cooperation, yet, communicable diseases, at least in the short term, have little or no effects on either.

Life cycle environmental impact assessment of natural gas distributed energy system

Natural gas distributed energy is recognized as a pivotal means to enhance energy efficiency and mitigate carbon dioxide emissions through localized energy cascading. Positioned as a key option for advancing the Sustainable Development Goals, this system optimizes energy utilization near end-users. While maximizing energy efficiency, it is imperative to address potential environmental challenges. A thorough, comprehensive environmental assessment, facilitated by the life cycle assessment method, proves instrumental in meeting this standard. Employing this method enables an intuitive grasp of the environmental strengths and weaknesses inherent in natural gas distributed energy within the power structure. This insight serves as a foundation for informed project decision-making, fostering the growth of the industry. We selected six environmental impact assessment categories based on the CML 2001 method, and conducted the life cycle analysis across four stages. China's inaugural natural gas distributed energy demonstration project was chosen as a model case, and an environmental impact assessment inventory was established, utilizing survey data and literature for comprehensive data collection and analysis. Results from case testing yield environmental impact assessment outcomes, with a specific sensitivity analysis for stages with notable environmental impact factors. The study underscores that the operation phase has the highest environmental impact, comprising 78.37% of the total combined environmental impact, followed by the fuel production phase. Comparative analyses with coal-fired and conventional natural gas power generation, based on dimensionless literature data, reveal that abiotic resources depletion potential is the primary contributor to the environmental impact of 1 kWh of electricity product, constituting 52.76% of the total impact value, followed by global warming potential. Concrete strategies have been outlined for decision-making in both the operational and planning phases of natural gas distributed energy projects. The strengthening of policies is pinpointed towards grid connection and scale expansion.

A nationwide time-series analysis for short-term effects of ambient temperature on violent crime in South Korea

Psychological theories on heat-aggression relationship have existed for decades and recent models suggest climate change will increase violence through varying pathways. Although observational studies have examined the impact of temperature on violent crime, the evidence for associations is primarily limited to coarse temporal resolution of weather and crime (e.g., yearly/monthly) and results from a few Western communities, warranting studies based on higher temporal resolution data of modern systemic crime statistics for various regions. This observational study examined short-term temperature impacts on violent crime using national crime data for the warm months (Jun.-Sep.) across South Korea (2016-2020). Distributed lag non-linear models assessed relative risks (RRs) of daily violent crime counts at the 70th, 90th, and 99th summer temperature percentiles compared to the reference temperature (10th percentile), with adjustments for long-term trends, seasonality, weather, and air pollution. Results indicate potentially non-linear relationships between daily summer temperature (lag0-lag10) and violent crime counts. Violent crimes consistently increased from the lowest temperature and showed the highest risk at the 70th temperature (~ 28.0 °C). The RR at the 70th and 90th percentiles of daily mean temperature (lag0-lag10), compared to the reference, was 1.11 (95% CI 1.09, 1.15) and 1.04 (95% CI 1.01, 1.07), indicating significant associations. Stratified analysis showed significant increases in assault and domestic violence for increases in temperature. The lagged effects, the influences of heat on subsequent crime incidence, did not persist 21 days after the exposure, possibly due to the displacement phenomenon. We found curvilinear exposure-response relationships, which provide empirical evidence to support the psychological theories for heat and violence. Lower public safety through increased violent crime may be an additional public health harm of climate change.

Sustaining energetic communities: energy citizenship and participation in an age of upheaval and transition

The human use of energy is inherently understood and experienced through socially constructed frameworks. However, the degree of engagement with this topic on the part of humanities and the social sciences has until recently been uneven at best. This seems strange given current upheavals experienced in Europe and across the globe as the climate and biodiversity crises deepen. At the centre of all these crises is the energy system. Energy flows through various forms of natural and social circuitry (from production, to distribution and consumption) and these energyscapes are sited at the local, national, and transnational scales. The correlation between the (meta)physical flows taken by the various forms of energy we depend on-and the transitory social, cultural, economic, and political relationships that frame them-require much deeper study if we are to achieve the types of sustainable communities envisaged by the United Nations as part of its sustainable development goals (SDGs) for 2030. Arising from a review of current literature, this article presents recent research into the forming of citizen energy communities in Europe and the governance structures designed to facilitate their development. It also highlights the key drivers and barriers to citizen engagement with emergent, novel energetic communities.

Fast hybrid methods for modeling landslide susceptibility in Ardal County

Recently, machine learning models have received huge attention for environmental risk modeling. One of these applications is landslide susceptibility mapping which is a necessary primary step for dealing with the landslide risk in prone areas. In this study, a conventional machine learning model called multi-layer perceptron (MLP) neural network is built upon advanced optimization algorithms to achieve a firm prediction of landslide susceptibility in Ardal County, West of Iran. The used geospatial dataset consists of fourteen conditioning factors and 170 landslide events. The used optimizers are electromagnetic field optimization (EFO), symbiotic organisms search (SOS), shuffled complex evolution (SCE), and electrostatic discharge algorithm (ESDA) that contribute to tuning MLP's internal parameters. The competency of the models is evaluated using several statistical methods to provide a comparison among them. It was discovered that the EFO-MLP and SCE-MLP enjoy much quicker training than SOS-MLP and ESDA-MLP. Further, relying on both accuracy and time criteria, the EFO-MLP was found to be the most efficient model (time = 1161 s, AUC = 0.879, MSE = 0.153, and R = 0.657). Hence, the landslide susceptibility map of this model is recommended to be used by authorities to provide real-world protective measures within Ardal County. For helping this, a random forest-based model showed that Elevation, Lithology, and Land Use are the most important factors within the studied area. Lastly, the solution discovered in this study is converted into an equation for convenient landslide susceptibility prediction.

Insights from international environmental legislation and protocols for the global plastic treaty

Plastic pollution has emerged as a global challenge necessitating collective efforts to mitigate its adverse environmental consequences. International negotiations are currently underway to establish a global plastic treaty. Emphasizing the need for solution-orientated research, rather than focusing on further defining the problems of widespread environmental occurrence and ecological impacts, this paper extracts insights and draws key patterns that are relevant for these international negotiations. The analysis reveals that (i) environmental rather than human health concerns have been the predominant driving force behind previous regulations targeting pollutants, and (ii) the decision to ban or discontinue the use of harmful pollutants is primarily affected by the availability of viable substitutes. These two key findings are relevant to the discussions of the ongoing Intergovernmental Negotiating Committee (INC) on the global plastic treaty and underscore the recognition of environmental consequences associated with plastic pollution while emphasizing the need to enhance the knowledge base of potential human health risks. Leveraging the availability of substitutes can significantly contribute to the development and implementation of effective strategies aimed at reducing plastic usage and corresponding pollution.

The role of ESG performance during times of COVID-19 pandemic

The outbreak of the epidemic in 2020 has caused a huge negative impact on the production and operation of firms, directly threatening their survival and development. However, some firms can make timely and effective adjustments in the face of sudden crises because of their resilience, and then turn the corner. This study selects the data of 2993 companies listed in Chinese A shares. The OLS method and event study is used to analyze the impact of ESG on the ability of corporate system crisis (corporate resilience). The research results indicate that companies with good ESG performance are more resilient in crises. The mechanism test indicates that the easing effect of corporate financing constraints and the expansion effect of corporate green innovation capabilities are important channels for ESG performance to promote the negative impact of crisis shocks on corporate value. Heterogeneity analysis indicates that ESG has a stronger ability to respond to systemic crises in small-scale firms, state-owned firms, and highly competitive market environments. Powerful CEOs can weaken ESG's ability to respond to systemic corporate crises. Further research has found that only S and G items, namely good governance level and social performance, have a significant positive promoting effect on corporate resilience. ESG performance may be more important in areas more severely affected by the epidemic. This study expands the research on ESG and the research on the decision mechanism of enterprise resilience. This study provides a new theoretical perspective for the study of corporate crisis response capabilities, and provides a certain policy reference for Chinese firms to effectively respond to public crises, which has important policy implications.

Determinants of household adoption of clean energy with its rural-urban disparities in Bangladesh

This study aims to investigate factors influencing the adoption of clean energy among households in Bangladesh, using Blinder-Oaxaca decomposition and extended probit regression model with data from the 2019 Bangladesh multiple indicator cluster survey. Small households, primarily Muslim and urban dwellers, who speak the Bengali language and are Internet and mobile users, were likelier to adopt cleaner fuels than their counterparts. On the contrary, households residing in the Barisal, Khulna, Rajshahi, and Rangpur divisions, belonging to poor and middle-class households, with household heads aged 15-64 and without formal education, were less likely to adopt cleaner fuels than their counterparts. The concentration curve revealed socioeconomic inequality in the adoption of clean energy, particularly favouring richer households in urban and rural areas. Further analysis using the Blinder-Oaxaca decomposition showed that urban residents showed a higher probability of adopting clean energy, with a significant difference of 0.508 compared to rural areas. Regarding the endowment effect, poor wealth quintile contributed the most, followed by the ownership of rented dwellings and the middle wealth quintile. The Bengali differential effect made the largest contribution to this aspect of the disparity, followed by the exposure of the Internet and the influence of the Dhaka and Chattogram divisions. The detailed analysis provides valuable insights for policymakers and practitioners on the issue of disparities in the adoption of clean energy between urban and rural areas in Bangladesh.

Prediction of atmospheric PM2.5 level by machine learning techniques in Isfahan, Iran

With increasing levels of air pollution, air quality prediction has attracted more attention. Mathematical models are being developed by researchers to achieve precise predictions. Monitoring and prediction of atmospheric PM2.5 levels, as a predominant pollutant, is essential in emission mitigation programs. In this study, meteorological datasets from 9 years in Isfahan city, a large metropolis of Iran, were applied to predict the PM2.5 levels, using four machine learning algorithms including Artificial Neural |Networks (ANNs), K-Nearest-Neighbors (KNN), Support Vector |Machines (SVMs) and ensembles of classification trees Random Forest (RF). The data from 7 air quality monitoring stations located in Isfahan City were taken into consideration. The Confusion Matrix and Cross-Entropy Loss were used to analyze the performance of classification models. Several parameters, including sensitivity, specificity, accuracy, F1 score, precision, and the area under the curve (AUC), are computed to assess model performance. Finally, by introducing the predicted data for 2020 into ArcGIS software and using the IDW (Inverse Distance Weighting) method, interpolation was conducted for the area of Isfahan city and the pollution map was illustrated for each month of the year. The results showed that, based on the accuracy percentage, the ANN model has a better performance (90.1%) in predicting PM2.5 grades compared to the other models for the applied meteorological dataset, followed by RF (86.1%), SVM (84.6%) and KNN (82.2%) models, respectively. Therefore, ANN modelling provides a feasible procedure for the managerial planning of air pollution control.

The process of social death in patients with hip fracture

People with chronic disability and uncontrollable long-term complications following hip fracture have characterist.ics that may predispose them to social death. Continuous physical disability can have negative physical, psychological, and social consequences in these patients. To design care interventions for preventing and controlling social death, it is essential to identify the dimensions and characteristics of this process. Therefore, the present study aimed to explain the process of social death in hip fracture patients. In this study, which was conducted using a grounded theory approach, 20 patients were selected with maximum diversity and 9 professional and non-professional caregivers also through purposive sampling followed by theoretical sampling. Data were collected through semi-structured in-depth interviews, field notes, and observations. Data were analyzed using the approach proposed by Corbin and Strauss in stages including data analysis for concepts and their dimensions and characteristics, the context, process extraction, and integration of the categories. One core category and 16 main categories, which consisted of 55 subcategories and 212 primary concepts, were extracted. The results showed that the core process of social death in hip fracture is an intentional self-destruction for getting liberated from the conditions of the illness and the disrupted social life after the fracture, which ultimately leads to outcomes such as isolation-seeking and death ideations in these patients. The core category of liberating self-destruction reflects the close relationship between the context, process, and outcomes of social death. The process of social death is social, multidimensional, and complex. So far, no explanatory theory has been presented for this group of patients. Therefore, the results of this study can play an important role in designing helpful interventions for preventing, modifying, and changing the phenomenon of social death.

Predicting sustainable fashion consumption intentions and practices

The fashion industry has a significant impact on the environment, and sustainable fashion consumption (SFC) has become a pressing concern. This study aimed to investigate the factors influencing sustainable fashion consumption behavior (SCB) among Chinese adults, specifically the role of values, attitudes, and norms in shaping such behavior, using the value-belief-norm framework. The study used an online cross-sectional survey design to collect data from 350 participants recruited through a convenience sampling method using social media platforms and email invitations, and the obtained data were analyzed using partial least squares structural equation modelling. The results of the study showed that biospheric (BV), altruistic (AV), and egoistic (EV) values significantly influenced the New ecological paradigm (EP), which, in turn, positively affected awareness of consequences (AC). Personal norms (PN) were positively influenced by EP, AC, and ascription of responsibility (AR). Social norms (SN) and trust in recycling (TR) were also found to positively influence sustainable fashion consumption intentions (SCI). Finally, the study found that SCI and TR were significant predictors of SCB, whereas the moderating effect of TR not statistically significant. The study's originality lies in its comprehensive investigation of the interplay between various factors (particularly using norms in two facets; PN and SN) in shaping SCB, using a structural equation modeling approach, and exploring the moderating effect of TR. The findings of this study suggest that interventions aimed at promoting SFC should focus on fostering values and beliefs that prioritize the environment, encouraging individuals to take responsibility for their actions, creating an environment in which SFC is normalized, and increasing TR.

Environmental and health values, beliefs, norms and compatibility on intention to adopt hydroponic farming among unemployed youth

The objective of this study was to examine the relationships among environmental and health values, ecological worldview, perception of consequences, the ascription of responsibility, and personal norms in the context of the value-belief-norm (VBN) model and how compatibility influences the intentions and behaviors of Chinese youth regarding the use of hydroponic farming technology. The study employed a survey questionnaire to collect data from the target population. The sample size was determined through a power analysis to ensure sufficient statistical power for the analysis. A total of 727 potential respondents' responses were analyzed using SmartPLS (4.0) to perform structural equation modeling. The results confirmed that environmental, emotional, and health values significantly associated with individuals' ecological worldviews. There was an interconnection between ecological worldview, awareness of consequences, and ascription of responsibility, and all three significantly influenced personal norms. The key determinants of the intentions and behaviors to adopt hydroponic farming technology are personal norms and technology compatibility. Therefore, to promote and motivate the interest and intention to use hydroponics among unemployed youth, government agencies, and related companies should focus on providing technology-related and pro-environmental information and training. This is expected to increase the acceptance and awareness of hydroponics among this group, thus increasing the adoption rate of hydroponics.

Geodetector analysis of individual and joint impacts of natural and human factors on maternal and child health at the provincial scale

This ecological study examined the individual and joint impacts of natural-human factors on the spatial patterns of maternal and child health status in China at the provincial scale in 2020. We considered natural factors (forest coverage, average temperature, and total sulfur dioxide and particulate matter emissions) and human factors (economic development, urbanization, healthcare access, and education level). We combined maternal, infant, and under-five mortality rates into a composite maternal and child health index using the entropy method. The spatial autocorrelation analysis of this index highlighted distinct health patterns across provinces, whereas the geodetector method assessed the effects of natural-human factors on the patterns. A notable east-central-west stepwise decline in health status was observed. Global Moran's I showed positive spatial clustering, with high-high clustering areas in the Yangtze River Delta and low-low clustering areas in western regions. Factor detection identified eight significant natural-human factors impacting maternal and child health, with total sulfur dioxide emission density having the greatest impact. The interaction between average schooling years and total sulfur dioxide emission notably affected maternal and child health patterns. The study concludes that natural-human factors critically affect the spatial distribution of maternal and child health.

An environmental justice analysis of air pollution emissions in the United States from 1970 to 2010

Over the last decades, air pollution emissions have decreased substantially; however, inequities in air pollution persist. We evaluate county-level racial/ethnic and socioeconomic disparities in emissions changes from six air pollution source sectors (industry [SO2], energy [SO2, NOx], agriculture [NH3], commercial [NOx], residential [particulate organic carbon], and on-road transportation [NOx]) in the contiguous United States during the 40 years following the Clean Air Act (CAA) enactment (1970-2010). We calculate relative emission changes and examine the differential changes given county demographics using hierarchical nested models. The results show racial/ethnic disparities, particularly in the industry and energy generation source sectors. We also find that median family income is a driver of variation in relative emissions changes in all sectors-counties with median family income >$75 K vs. less generally experience larger relative declines in industry, energy, transportation, residential, and commercial-related emissions. Emissions from most air pollution source sectors have, on a national level, decreased following the United States CAA. In this work, we show that the relative reductions in emissions varied across racial/ethnic and socioeconomic groups.

Association between serum heavy metal levels and diabetic retinopathy in NHANES 2011-2020

The present study utilized the National Health and Nutrition Examination Survey (NHANES) database to examine the relationship between serum levels of heavy metals and Diabetic retinopathy (DR) in individuals aged over 30 years with type 2 diabetes mellitus (T2DM) in the United States. A cross-sectional analysis was conducted on 1583 individuals with T2DM from the NHANES 2011-2020, including 331 individuals in the DR group and 1252 individuals in the non-DR group. We collected data on serum levels of heavy metals, DR, and serum albumin for descriptive statistics, linear regression, and logistical regression analysis. After adjusting for age, gender, race and other factors, there was no statistically significant association between blood cadmium, selenium, mercury, or lead and DR. However, serum manganese (Mn) and DR had a significant negative association (β = - 0.2045, 95% CI = - 0.3484, - 0.0606). Serum albumin partially modulated the indirect influence of serum Mn on the incidence of DR, accounting for 12.80% of the association between serum Mn and DR. There was a negative association between serum Mn levels and the prevalence of DR in people with T2DM. Mn intake at least in this study has a little influence on the onset and development of DR.

New approach into human health risk assessment associated with heavy metals in surface water and groundwater using Monte Carlo Method

This study assessed the environmental and health risks associated with heavy metals in the water resources of Egypt's northwestern desert. The current approaches included the Spearman correlation matrix, principal component analysis, and cluster analysis to identify pollution sources and quality-controlling factors. Various indices (HPI, MI, HQ, HI, and CR) were applied to evaluate environmental and human health risks. Additionally, the Monte Carlo method was employed for probabilistic carcinogenic and non-carcinogenic risk assessment via oral and dermal exposure routes in adults and children. Notably, all water resources exhibited high pollution risks with HPI and MI values exceeding permissible limits (HPI > 100 and MI > 6), respectively. Furthermore, HI oral values indicated significant non-carcinogenic risks to both adults and children, while dermal contact posed a high risk to 19.4% of samples for adults and 77.6% of samples for children (HI > 1). Most water samples exhibited CR values exceeding 1 × 10-4 for Cd, Cr, and Pb, suggesting vulnerability to carcinogenic effects in both age groups. Monte Carlo simulations reinforced these findings, indicating a significant carcinogenic impact on children and adults. Consequently, comprehensive water treatment measures are urgently needed to mitigate carcinogenic and non-carcinogenic health risks in Siwa Oasis.

A fresh perspective on infrared spectroscopy as a prescreening method for molecular and stable isotopes analyses on ancient human bones

Following the development of modern genome sequencing technologies, the investigation of museum osteological finds is increasingly informative and popular. Viable protocols to help preserve these collections from exceedingly invasive analyses, would allow greater access to the specimens for scientific research. The main aim of this work is to survey skeletal tissues, specifically petrous bones and roots of teeth, using infrared spectroscopy as a prescreening method to assess the bone quality for molecular analyses. This approach could overcome the major problem of identifying useful genetic material in archaeological bone collections without resorting to demanding, time consuming and expensive laboratory studies. A minimally invasive sampling of archaeological bones was developed and bone structural and compositional changes were examined, linking isotopic and genetic data to infrared spectra. The predictive model based on Infrared parameters is effective in determining the occurrence of ancient DNA (aDNA); however, the quality/quantity of aDNA cannot be determined because of the influence of environmental and local factors experienced by the examined bones during the burial period.

Impact of weather and climate advisories on agricultural outcomes in Pakistan

The earth is warming, and the frequency of extreme weather events have been rapidly growing globally with unprecedented consequences to farming communities. In principle, weather and climate information services (WCIS) can help farmers better manage their activities and farm level outcomes by supporting their decision-making with relevant and usable information to address the potential impacts of expected changing climate conditions. But, in practice, can the availability and use of WCIS help improve agricultural outcomes given the weather and climate related uncertainties? To understand the use and impact of WCIS in the cotton-wheat cropping areas of Pakistan, we conducted a multistage stratified clustered random sample of 612 farm households in the provinces of Punjab and Sindh. Over 55% of the farm households in the sample indicated that they used WCIS provided by the Pakistan Meteorological Department and other sources for making their agricultural decisions. Our analysis, however, suggests that the impact of using WCIS on major farm outcomes (i.e. farm revenue, costs, profits, and input usage) is not statistically significant when compared with those farm households not using WCIS (null result). This result is robust to different estimation techniques (i.e. ordinary least squares, instrumental variable approach, and propensity score matching method). From the focus group discussions, we gathered that farmers perceived WCIS as less reliable, often unclear, and difficult to understand as this information is not translated and transmitted in local languages. Addressing these issues can help reduce the impact of climate and weather variability on farm outcomes in those provinces as well as in Pakistan more generally. Our study suggests that, under uncertainty, emphasis should be on WCIS that farmers can rely on for making farming related decisions.

A stochastic programming approach for EOL electric vehicle batteries recovery network design under uncertain conditions

With the development of the electric vehicle industry, the number of power batteries has increased dramatically. Establishing a recycling EOL (end-of-life) battery network for secondary use is an effective way to solve resource shortage and environmental pollution. However, existing networks are challenging due to the high uncertainty of EOL batteries, e.g., quantity and quality, resulting in a low recycling rate of the recovery network. To fill this gap, this paper proposes a stochastic programming approach for recovery network design under uncertain conditions of EOL batteries. Firstly, a multi-objective model for battery recovery network is established, considering carbon emissions and economic benefits. Secondly, a stochastic programming approach is proposed to clarify the model. Subsequently, the genetic algorithm is employed to solve the proposed model. Finally, a recovery network case of Region T is given to verify the credibility and superiority of the proposed method. The results demonstrate that the proposed model reduces carbon emissions by 20 metric tons and increases overall economic benefits by 10 million yuan in Region T compared to the deterministic model. Furthermore, the two portions affecting the optimization results are also discussed to provide a reference for reducing carbon emissions and improving economic efficiency in recycling networks.

Coastal vulnerability assessment of the West African coast to flooding and erosion

Global coastal areas are at risk due to geomorphological issues, climate change-induced sea-level rise, and increasing human population, settlements, and socioeconomic activities. Here, the study examines the vulnerability of the West African (WA) coast using six satellite-derived geophysical variables and two key socioeconomic parameters as indicators of coastal vulnerability index (CVI). These geophysical and socioeconomic variables are integrated to develop a CVI for the WA coast. Then, the regional hotspots of vulnerability with the main indicators that could influence how the WA coast behaves and can be managed are identified. The results indicate that 64, 17 and 19% of WA coastal areas had high to very high CVI, moderate CVI, and low to very low CVI, respectively. The study reveals that while geophysical variables contribute to coastal vulnerability in WA, socioeconomic factors, particularly high population growth and unsustainable human development at the coast, play a considerably larger role. Some sections of the WA coast are more vulnerable and exposed than others, particularly those in the region's northwestern and Gulf of Guinea regions. Climate change and human presence may amplify the vulnerability in these vulnerable areas in the future. Hence, future coastal economic development plans should be based on a deep understanding of local natural conditions, resource status, and geophysical parameters to prevent negative coastal ecosystem transformation. It is also essential to establish a coastal management plan that would facilitate the development of desired actions and stimulate sustainable management of West African coastal areas.

Boil water notices as health-risk communication: risk perceptions, efficacy, and compliance during winter storm Uri

Winter Storm Uri was a disaster that impacted much of the United States during February of 2021. During and after the storm, Texas and Oklahoma experienced massive power grid failures. This led to cascading impacts, including water system disruptions and many boil water notices (BWNs). The breakdown of some communication channels and the inability to enact protective actions due to power outages, as well as travel limitations on public roads, complicated the dissemination and implementation of notifications. This research examined individuals' perceptions of risk, water quality, and BWNs during Uri. Additionally, this study sought to understand if previous experience with a BWN influenced compliance during Uri and how perceived efficacy impacted these variables. Surveying 893 Texans and Oklahomans revealed that most Uri-affected respondents believed the risks associated with BWNs were severe. Income and race were two factors that influenced BWN compliance. Age, gender, and level of education did not influence compliance. Previous experience with BWNs did not increase risk perceptions. Higher levels of perceived efficacy correlated to higher levels of compliance, perceptions of risk, and water quality, much of which support propositions of the Extended Parallel Process Model. Results suggest that pre-disaster planning and communication are imperative to helping reduce risk(s) and enhancing efficacy during a disaster, especially for novel disasters that have cascading risks, like Winter Storm Uri.

Behavioural factors matter for the adoption of climate-smart agriculture

Increasing agricultural productivity while ensuring environmental sustainability are two important targets in achieving the sustainable development goals under climatic shocks. In this regard, different climate-smart agricultural (CSA) practices have been recommended and promoted to meet these goals and targets. However, the adoption of these practices remains low and variable. For the most part, low adoption has been attributed to external factors. Behavioural and psychological factors also matter but have received little empirical and policy attention. In this study, we examine the relationship between aspirations, aspiration gaps, and the adoption of CSA practices such as crop rotation, intercropping, fallowing, and organic soil amendments. Employing parametric and non-parametric estimation techniques on a pooled farm household survey from Cameroon and Kenya, we show that aspirations are associated with the use of crop rotation and organic soil amendments. We also investigate the theorized non-monotonic inverse U-shaped relationship between aspiration gaps and investments. We find evidence of this relationship for the adoption of these CSA practices, suggesting an aspiration failure for smallholder farmers. These results imply that aspirations that are ahead but not too far ahead of the current state serve as the best incentives for stimulating the adoption of CSA practices. Employing the multivariate probit model, we further highlight interdependencies in the use of these CSA practices. Specifically, we underscore significant complementarities, suggesting the bundled use of these practices. Overall, the analysis demonstrates that aspirations matter for farmer decision-making with many implications for agricultural, food, and environmental policies.

The impact of digital transformation and earnings management on ESG performance: evidence from Chinese listed enterprises

The improvement of enterprise ESG performance is one of the key driving forces to achieve the goal of economic and social green development. There is a gap between knowledge and practice in the ESG performance of Chinese enterprises, and digital transformation (DT) provides new ideas for ESG development. The research purpose of this paper is to explore the impact mechanism of DT on ESG and the specific path of DT to drive ESG. It provides a reference for listed enterprises to rely on DT to empower their sustainable development capability. This paper takes the panel data of A-share listed enterprises from 2011 to 2021 as the sample and measures the core indicators using the text mining method, modified Jones model, and Roy-Chowdhury model. On this basis, using a combination of econometric models and qualitative comparative analysis, we empirically analyze the impact mechanisms of DT on ESG as well as the specific grouping paths that drive ESG performance. The main conclusions are shown as follows. First, DT can significantly reduce ESG, with an impact coefficient of - 0.013, which is significant at the 5% level. It reflects that the DT of enterprises at this stage has certain deficiencies. There is a matching lag in the enterprise's internal organizational resources. The entry of digital technology will have a certain impact on traditional operations, and the high uncertainty of DT adds some hidden costs to the enterprise. Secondly, there is an indirect suppression effect of accrued earnings management (AEM) in the transmission mechanism of DT affecting ESG. It is verified that DT can reduce information asymmetry and inhibit EM activities, thus reducing the impact on ESG. Finally, a total of six configurations achieved high ESG valuations. High technology practice-low performance manipulation; digital intelligence-low performance manipulation; digital intelligence-digital resources; digital resources-inadequate digital infrastructure.; high technology practice-bottom technology deficiency; digital intelligence-high performance manipulation. Through configuration analysis, the suppression effect of EM is further verified. The lack of AEM is usually the core condition of the high-valuation group. Meanwhile, digital intelligence, digital resources, and digital technology practice can drive the improvement of enterprise ESG. The instrumental variables approach and robustness tests support these findings.

A database of mapped global fishing activity 1950-2017

A new database on historical country-level fishing fleet capacity and effort is described, derived from a range of publicly available sources that were harmonized, converted to fishing effort, and mapped to 30-min spatial cells. The resulting data is comparable with widely used but more temporally-limited satellite-sourced Automatic Identification System (AIS) datasets for large vessels, while also documenting important smaller fleets and artisanal segments. It ranges from 1950 to 2017, and includes information on number of vessels, engine power, gross tonnage, and nominal effort, categorized by vessel length, gear type and targeted functional groups. The data can be aggregated to Large Marine Ecosystem, region and/or fishing country scales and provides a temporally and spatially explicit source for fishing effort and fleet capacity for studies aimed at understanding the implications of long-term changes in fishing activity in the global ocean.

The impact of the digital economy on urban total factor productivity: mechanisms and spatial spillover effects

Digital economy is the indispensable pathway for driving industrial structural upgrading and fostering innovation and entrepreneurship in cities, ultimately facilitating China's economic transformation. Simultaneously, the enhancement of urban total factor productivity (TFP) serves as a crucial means to achieve high-quality economic development in cities. This study examines the specific impact of the digital economy on urban TFP using a panel data model with a sample of 285 Chinese prefecture-level cities from 2011 to 2019. Additionally, it employs a mediation effect model to test the mechanisms through which the digital economy influences urban TFP and utilizes a spatial Durbin model to analyze the spatial spillover effects of the digital economy on urban TFP. The research findings reveal the following key points: (1)The digital economy has an overall significantly positive impact on urban TFP. (2)The digital economy indirectly promotes urban TFP by encouraging the advancement of industrial structure and fostering innovation and entrepreneurship in cities. (3)The influence of the digital economy on urban TFP exhibits spatial spillover effects, where the digital economy in neighboring cities significantly enhances the TFP growth of local cities.The results of this study contribute to elucidating the mechanistic pathways through which the digital economy affects urban TFP, holding significant practical implications for achieving high-quality economic development in urban areas.

Research on the synergistic effects of urbanization and ecological environment in the Chengdu-Chongqing urban agglomeration based on the Haken model

The development of urbanization and the protection of the ecological environment are important aspects of sustainable development in urban agglomerations; thus, their coordination and synergy are crucial. Scholars in both China and other countries have conducted extensive research on the relationship between urbanization and the ecological environment from the perspective of coordinated development. However, there is a lack of research on the synergistic effects of urbanization and the ecological environment. Taking the Chengdu-Chongqing urban agglomeration as an example, this study uses the Haken model to analyze the synergistic evolution mechanism, development patterns, and future trends of urbanization and the ecological environment. This study draws the following conclusions: (1) while a synergistic development mechanism has been established between urbanization and the ecological environment, the current system is still in a stage of low-level synergy, and the control system's parameter for the direction and path of evolution is urbanization. (2) From 2001 to 2020, the level of synergistic development between urbanization and the ecological environment was relatively low, mainly moving from low-level synergy to medium-low-level synergy to medium-level synergy. (3) There is a significant spatial disparity in the levels of synergistic development, for which the leading region centers on Chengdu and Chongqing in the northwest and southeast, respectively, and the lagging region comprises the eastern part of the urban agglomeration, mainly represented by Dazhou, Kaizhou, and Yunyang. (4) The future trend of synergistic development between urbanization and the ecological environment in the Chengdu-Chongqing urban agglomeration is promising but requires increased infrastructure construction in mountainous urban areas, enhanced cooperation and circulation in transportation, logistics, information and other aspects, and balanced improvements in the level of synergistic development between urbanization and the ecological environment. The study of the synergistic development effect of urbanization and the ecological environment in urban agglomerations is of great significance for reducing the negative impact of urbanization on the ecological environment, increasing the positive interaction between the two, and promoting sustainable development in urban agglomerations.

Passenger muscle responses in emergency braking events with reclined seating

Emergency braking can generate forward displacement that may influence the effectiveness of protection in collisions, especially for passengers. The development of automated vehicles has enabled the diversification and rationalization of sitting positions, including reclined seating. However, the passenger response in pre-crash scenarios in reclined seating differs from that in standard seating, which poses different requirements for biofidelic human body models (HBMs) to evaluate passenger injuries in collisions. This study conducted emergency braking trials in vehicles at an initial velocity of 80 km/h. Five volunteers were exposed to approximately 1 g manual emergency braking (MEB), and the muscle responses at the front passenger seat with backrest angles of 25°, 45°, and 65° were recorded. The electromyography obtained from 14 muscles of the neck, torso, and lower extremity were normalized using maximum voluntary contractions (MVCs). In the quiet sitting phase, the activity levels were low (< 5% MVC) in all muscles for the three sitting positions. During emergency braking, the muscles are activated to restrict the body motion. There were differences in muscle amplitude and onset time in different backrest angles, with higher muscle activity levels in most muscles in a reclined sitting position. In particular, the sternocleidomastoid, rectus abdominis, and vastus medialis showed different patterns in the peak and steady-state phases. We found that the tibialis anterior was consistently activated at a lower level in all sitting postures (< 8% MVC), which indicates limited support of the shank for the body. The data provided in the paper are presented in corridors and intended for use in the development and validation of HBMs with active muscle models to simulate evasive maneuvers that potentially occur before a crash in the reclined sitting position.

Integrated approach to water resource management in Mashhad Plain, Iran: actor analysis, cognitive mapping, and roadmap development

Iran's Mashhad Plain faces a severe water crisis due to the excessive exploitation of groundwater, leading to the depletion of its aquifer. While water demand management is recognized as a superior solution compared to supply projects, its implementation presents notable challenges. This study addresses the urgent necessity to curtail water demand in the Mashhad Plain by alleviating conflicts among various stakeholders, including water resource managers and consumers. Initially, the research identifies key water resource actors who collaborate in devising a comprehensive roadmap and conceptual model for efficient water resource management. An analysis uncovers significant conflicts among actors, representing approximately 6% of identified issues, with minor conflicts in 30% of cases. Encouragingly, stakeholders demonstrate potential for consensus on the remaining conflict items, with specific actors emerging as pivotal in conflict resolution. Efficient water resource management in regions facing scarcity, diverse interests, and sustainability challenges demands a multifaceted strategy. Future endeavors involve developing a dynamic system model to simulate policy impacts and strengthen conflict resolution efforts. This research introduces a roadmap-driven approach aimed at resolving conflicts and implementing water demand management in the Mashhad Plain. It emphasizes the critical need to address water scarcity challenges while effectively mitigating conflicts among water resource stakeholders.

Longitudinal population-level HIV epidemiologic and genomic surveillance highlights growing gender disparity of HIV transmission in Uganda

HIV incidence in eastern and southern Africa has historically been concentrated among girls and women aged 15-24 years. As new cases decline with HIV interventions, population-level infection dynamics may shift by age and gender. Here, we integrated population-based surveillance of 38,749 participants in the Rakai Community Cohort Study and longitudinal deep-sequence viral phylogenetics to assess how HIV incidence and population groups driving transmission have changed from 2003 to 2018 in Uganda. We observed 1,117 individuals in the incidence cohort and 1,978 individuals in the transmission cohort. HIV viral suppression increased more rapidly in women than men, however incidence declined more slowly in women than men. We found that age-specific transmission flows shifted: whereas HIV transmission to girls and women (aged 15-24 years) from older men declined by about one-third, transmission to women (aged 25-34 years) from men that were 0-6 years older increased by half in 2003 to 2018. Based on changes in transmission flows, we estimated that closing the gender gap in viral suppression could have reduced HIV incidence in women by half in 2018. This study suggests that HIV programmes to increase HIV suppression in men are critical to reduce incidence in women, close gender gaps in infection burden and improve men's health in Africa.

The urban heat island under extreme heat conditions: a case study of Hannover, Germany

Global warming has resulted in higher frequencies of climate extremes, such as drought periods or heat waves. Heat waves are intensified in urban areas due to the urban heat island effect. Studies are inconclusive as to whether the urban heat island effect is intensified during heat waves. Using the city of Hannover, Germany, as a case study, we analysed the intensity of the urban heat island under unprecedented summer heat conditions in the years 2018, 2019 and 2020, which were among the hottest in Germany since weather records began. We compared the intensity of the urban heat island across these years with the non-heat year of 2017. Differences were analysed for various inner-city urban locations and an urban park, while accounting for their distinct land use and land cover characteristics. We identified the urban heat island effect across all years investigated in the study and also found a significant intensified urban heat island effect during the years of unprecedented heat, when night-time temperature minima are considered. The urban heat island was identified on a lower level, however, with maximum daily temperatures when compared to the non-heat year. The lowest intensity of the urban heat island was found for the urban park site, highlighting the need for more city-wide greening strategies, including tree-covered and open green spaces, to provide all residents with the cooling services of green spaces.