The National Weather Service of the United States uses the heat index—a combined measure of temperature and relative humidity—to define risk thresholds warranting the issuance of public heat alerts. We use statistically downscaled climate models to project the frequency of and population exposure to days exceeding these thresholds in the contiguous US for the 21st century with two emissions and three population change scenarios. We also identify how often conditions exceed the range of the current heat index formulation. These 'no analog' conditions have historically affected less than 1% of the US by area. By mid-21st century (2036–2065) under both emissions scenarios, the annual numbers of days with heat indices exceeding 37.8 °C (100 °F) and 40.6 °C (105 °F) are projected to double and triple, respectively, compared to a 1971–2000 baseline. In this timeframe, more than 25% of the US by area would experience no analog conditions an average of once or more annually and the mean duration of the longest extreme heat index event in an average year would be approximately double that of the historical baseline. By late century (2070–2099) with a high emissions scenario, there are four-fold and eight-fold increases from late 20th century conditions in the annual numbers of days with heat indices exceeding 37.8 °C and 40.6 °C, respectively; 63% of the country would experience no analog conditions once or more annually; and extreme heat index events exceeding 37.8 °C would nearly triple in length. These changes amount to four- to 20-fold increases in population exposure from 107 million person-days per year with a heat index above 37.8 °C historically to as high as 2 billion by late century. The frequency of and population exposure to these extreme heat index conditions with the high emissions scenario is roughly twice that of the lower emissions scenario by late century.
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Kristina Dahl et al 2019 Environ. Res. Commun. 1 075002
Simon Davidsson Kurland 2020 Environ. Res. Commun. 2 012001
Estimates of energy use for lithium-ion (Li-ion) battery cell manufacturing show substantial variation, contributing to disagreements regarding the environmental benefits of large-scale deployment of electric mobility and other battery applications. Here, energy usage is estimated for two large-scale battery cell factories using publicly available data. It is concluded that these facilities use around 50–65 kWh (180–230 MJ) of electricity per kWh of battery capacity, not including other steps of the supply chain, such as mining and processing of materials. These estimates are lower than previous studies using data on pilot-scale or under-utilized facilities but are similar to recent estimates based on fully utilized, large-scale factories. The environmental impact of battery manufacturing varies with the amounts and form of energy used; especially as renewable sources replace electricity from fossil fuels. As additional large-scale battery factories are taken into use, more data should become available, and the reliance on outdated, unrepresentative, and often incomparable, estimates of energy usage in the emerging Li-ion battery industry should be avoided.
Emily Rehberger et al 2023 Environ. Res. Commun. 5 052001
Regenerative agriculture aims to increase soil organic carbon (SOC) levels, soil health and biodiversity. Regenerative agriculture is often juxtaposed against 'conventional' agriculture which contributes to land degradation, biodiversity loss, and greenhouse gas emissions. Although definitions of regenerative agriculture may vary, common practices include no or reduced till, cover cropping, crop rotation, reduced use or disuse of external inputs such as agrichemicals, use of farm-derived organic inputs, increased use of perennials and agroforestry, integrated crop-livestock systems, and managed grazing. While the claims associated with some of these practices are supported by more evidence than others, some studies suggest that these practices can be effective in increasing soil organic carbon levels, which can have positive effects both agriculturally and environmentally. Studies across these different regenerative agriculture practices indicate that the increase in soil organic carbon, in comparison with conventional practices, varies widely (ranging from a nonsignificant difference to as high as 3 Mg C/ha/y). Case studies from a range of regenerative agriculture systems suggest that these practices can work effectively in unison to increase SOC, but regenerative agriculture studies must also consider the importance of maintaining yield, or risk the potential of offsetting mitigation through the conversion of more land for agriculture. The carbon sequestration benefit of regenerative practices could be maximized by targeting soils that have been intensively managed and have a high carbon storage potential. The anticipated benefits of regenerative agriculture could be tested by furthering research on increasing the storage of stable carbon, rather than labile carbon, in soils to ensure its permanence.
Haider Taha 2024 Environ. Res. Commun. 6 035016
Cool pavements represent one of several strategies that can mitigate the effects of urban overheating by increasing albedo. By definition, this means increasing reflected and potentially re-absorbed short-wave radiation but also decreased surface and air temperatures and longwave upwelling, thus reducing radiant temperatures. So far, real-world studies have been inconclusive as to net effects from cool pavements. A project by GAF installed reflective pavements in Pacoima, California, in summer of 2022. This study set out to perform detailed, high spatiotemporal resolution, multi-platform observations to quantify micrometeorological benefits of the cool pavements and address concerns regarding glare, chemistry/air quality, and pedestrian thermal comfort. Results indicated large variability, as expected, but that the dominant effects were beneficial both in direct side-by-side, real-time comparisons (RT) between test and reference areas, as well as in difference-of-difference (DofD) to quantify local changes in test areas. During a heatwave in September 2022, maximum air-temperature differences (averaged over individual street segments) reached up to −1.9 °C RT in the afternoon. During non-heatwave, hot summer days, the largest street-segment-averaged afternoon air-temperature differences reached up to −1.4 °C RT or −2.8 °C DofD, and surface temperature up to −9.2 °C RT or −12.2 °C DofD. Whereas above values represent maximum effects, more typical street-segment averages also showed statistically significant benefits. In the afternoon, the mean of air-temperature differences was −0.2 °C RT and −1.2 °C DofD. The mean of surface-temperature differences was −2.6 °C RT and −4.9 °C DofD. Indicators of pedestrian thermal comfort also showed variability but predominantly a cooling effect. The mean of differences in mean radiant temperature was between −0.9 and −1.3 °C RT, and for physiological equivalent temperature, between −0.2 °C and −0.6 °C RT and −1.7 °C DofD. In terms of predicted mean vote, the mean of differences was −0.09 RT and −0.32 DofD.
Niloufar Nouri and Naresh Devineni 2022 Environ. Res. Commun. 4 021001
This study presents an assessment of the spatial and temporal characteristics of large tornado outbreak (LTOs) days, in which several counties were impacted by tornadoes rated F2(EF2) or greater on the Fujita (Enhanced Fujita) scale in one day. A statistical evaluation of changes in the LTO clusters for two periods, 1950–1980 and 1989–2019, has been performed. There is a geographical shift of the nucleus (central impact location) towards the southeast United States. This spatial shift is also accompanied by reduced spatial variance, suggesting LTOs have become less dispersed (or more localized) in the recent period. The overall inter-arrival rate of LTOs, and how it changed during successive 31-year climatological blocks between 1950–2019 was investigated using an exponential probability model. The arrival rate has changed from 124 days during 1950–1980 to 164 days during 1977–2007 and remained relatively constant during later periods, indicating that LTOs are becoming less frequent.
Jagmohan Sharma and Nijavalli H Ravindranath 2019 Environ. Res. Commun. 1 051004
The Intergovernmental Panel on Climate Change (IPCC), Working Group II Report (2014) presents vulnerability as a pre-existing characteristic property of a system. Accordingly, indicators for 'sensitivity' and 'adaptive capacity', which are internal properties of a system, are employed to assess it. Comparatively, the IPCC 2007 report includes 'exposure', an external factor, as the third component of vulnerability. We have compared the construct of vulnerability presented in IPCC 2007 and 2014 reports. It is argued that the results of vulnerability assessment obtained by adopting IPCC 2014 framework are practically more useful for reducing current vulnerability in preparedness to deal with an uncertain future. In the process, we have articulated the novel concepts of 'selecting hazard-relevant vulnerability indicators' and 'assessing hazard-specific vulnerability'. Use of these concepts improves the contextualization of an assessment and thereby the acceptability of assessment results by the stakeholders.
Yiannis Kountouris and Eleri Williams 2023 Environ. Res. Commun. 5 011003
Protests are frequently used to raise public awareness of environmental challenges and increase support for pro-environmental behavior and policy. In this paper we examine the influence of protests on environmental attitudes, focusing on Extinction Rebellion's April 2019 campaign of civil disobedience in the UK. Using individual-level survey data collected around the time of the protest, we exploit its exogeneity to the timing of survey response, to compare attitudes towards sustainable lifestyles, perceptions of own environmental impact, support for pro-environmental policy and behavior, and views about the severity and imminence of environmental crises, before and after the protest. There is evidence that the protest is related to lower probability of opposing pro-environmental behavior and policy, and lower willingness to pay a premium for environmentally friendly consumption. We do not find evidence that the protest alienated the public from sustainable lifestyles, influenced perceptions of personal environmental impact, or views about the imminence and severity of environmental crises. Results suggest the need for systematic study of the impact of environmental protests on the general public's environmental attitudes and behaviors.
Gabriela Y Porras et al 2020 Environ. Res. Commun. 2 021004
This study evaluates and provides guidance on improving the life cycle environmental performance of dishwashing in the typical U.S. household. Typical user behaviors and recommended best practices for manual dishwashing as well as machine dishwasher use are evaluated. A sensitivity analysis shows the influence of varying grid carbon intensity, water heater type, regional water scarcity, and behaviors such as pre-rinsing and machine loading on overall results. Use-phase behaviors are observed through a small-scale laboratory study. Dishwashing following typical manual and machine practices produces 5,620 and 2,090 kg CO2e life cycle greenhouse gas (GHG) emissions respectively based on washing 4 loads (8 place settings per load) a week for 10 years. Avoiding typical behaviors like pre-rinsing and selecting heated dry can decrease life cycle GHG emissions for machine dishwashing by 3% and 11%, respectively. The running tap style of manual dishwashing results in the highest life cycle GHG emissions of the alternatives in the lab study. Manual dishwashing has the potential to have the lowest GHG emmisions (1,610 kg) when recommended behaviors are followed, less than the 1,960 kg CO2e for recommended machine dishwasher use. When life cycle water consumption burdens are evaluated, typical manual and machine dishwashing use 34,200 and 16,300 gallons respectively and these results are contextualized to regions with different water scarcity. A life cycle cost (LCC) analysis finds that machine dishwashing costs more than manual dishwashing over a 10-year lifetime even if best practices are followed. However, when a user's time spent washing is valued, machine dishwashers pay for themselves within a year of use.
Sudarsan Bera et al 2024 Environ. Res. Commun. 6 055009
The unique in situ measurements of clouds and precipitation within the shallow and deep cumulus over the north-eastern Arabian Sea region during the Indian monsoon are illustrated in this study with a focus on droplet spectral parameters. The observational period showed a significant incursion of Arabian dust and the presence of giant cloud condensation nuclei (GCCN), modifying the cloud and precipitation spectral properties. Warm rain microphysics supported the mixed-phase development in these clouds and exhibited hydrometeors of snow, graupel and large aggregates as part of ice processes. Cloud base droplet number concentration is about 142 79 cm−3 which is one third of the cloud condensation nuclei (CCN) number concentration at 0.2% supersaturation. A rapid broadening of droplet size distribution (DSD) near to the cloud base was noted in contrast to polluted continental clouds. Relationship between the relative dispersion ( the ratio of DSD spectral width () to mean radius ()) and liquid water adiabatic fraction (AF) indicates that the entrainment effect has increased relative dispersion significantly (2–3 times larger) in these clouds. Effective radius () is found to be proportional to mean volume radius () with a proportionality constant () that varies between 1.0–1.6, depending on the spectral dispersion parameter. Drop size distributions for the small cloud droplets with size range 2–50 m and the large drizzle drops (or ice hydrometeors) with size range 100–6400 m are parameterized using the gamma function distributions useful for large-scale cloud models.
Kamal Islam et al 2024 Environ. Res. Commun. 6 055017
The hydrological characteristics of a watershed play a crucial role in shaping ecosystems within the Boreal zone and have a significant impact on regional environments. Knowing these characteristics, such as the distinctive topography, vegetation, soil composition, and climatic conditions in the Canadian Boreal ecozone, is essential for implementing sustainable water management. This study focuses on assessing the hydrological dynamics of the Upper Humber River Watershed (UHRW) in western Newfoundland, Canada, using the Soil and Water Assessment Tool (SWAT) model. The UHRW includes sub-basins and hydrological response units (HRUs), with diverse land uses, soil types, and slope characteristics. Key parameters influencing streamflow simulation were identified through sensitivity analysis, including the runoff curve number, the effective hydraulic conductivity, the temperature lapse rate, the soil evaporation compensation factor, and the available water capacity of the soil layer. The SWAT model, using data from the Reidville hydrometric station, shows favorable performance metrics, with R2 values of 0.79 and 0.83 during the calibration and evaluation periods, respectively. The model effectively captures seasonal and monthly flow patterns, displaying right-skewed distributions and seasonal variations. The analyzed hydrological parameters, such as precipitation, evaporation, transpiration, surface runoff, and groundwater flow, reveal their significant contributions to the water balance. The flow duration curve analysis indicates the model's capability to estimate peak and low flows, with slight under-prediction during the recession phase. Seasonal analysis further supports the model's performance, with positive Nash-Sutcliffe Efficiency (NSE) values ranging from 0.65 to 0.91. The study concludes that the SWAT model is suitable for simulating the hydrological processes in the studied watershed providing valuable insights for sustainable water resource management and decision-making in the UHRW. The results can be useful for other Boreal ecozone watersheds.
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Marta Piccioni et al 2024 Environ. Res. Commun. 6 065001
This study investigated the biodegradation behavior of cotton fabrics treated with polypyrrole, a polymer with conductive and antibacterial properties. Fabric samples were buried in compost-enriched soil for 10, 30 and 90 days. The biodegradation level was initially estimated by a visual inspection of the fibers and by the determination of the fabric weight loss. Other physical–chemical changes of fibers during the biodegradation process were analyzed by microscopy, thermal analyses and infrared spectroscopy. The surface resistivity of the fabrics was also measured. The results obtained comparing the bare cotton samples and the polypyrrole-added ones suggested that, on the one hand, polypyrrole hindered/delayed the biodegradation of cotton in compost-enriched soil, probably exercising its inherent antimicrobial feature during the first period of burial. On the other hand, over time, polypyrrole seemed to represent the first compound attacked by the microorganisms, preserving the cotton substrate. Despite the absence of dedicated literature regarding polypyrrole biodegradation, the mechanism hypothesized in this paper involves the loss of conjugation, as a consequence of de-doping, oxidized functionalities up to local cycle breaking.
Nicholas G Theis and Ryan Light 2024 Environ. Res. Commun. 6 061003
Social science research on the environment has grown exponentially in the past four decades alongside increasing awareness that environmental risks, such as climate change, cannot be understood by natural science interventions alone. While prior research examines how specific disciplines, like sociology, have attended to the environment or how specific problems have been engaged across disciplines, less attention has been offered to the entire landscape of research on the environment in the social sciences. In this article, we ask: What is the landscape of environmental social science? Focusing on 124,906 social scientific articles from the Web of Science, we analyze the relationship between journals publishing research on the environment. Specifically, we construct journal citation networks and topic models on bibliographic records from 1990 to 2022. Results suggest that journals form coherent communities associated with both disciplinary and interdisciplinary research topics, indicating that journal communities may be a central organizing feature of ESS. Moreover, research topics prevalent in this field have changed over time, potentially in relation to the ongoing neoliberalization of climate change politics. As scholars want to influence policy and industrial practice, their research implicitly reflects values consistent with the current political economic order. We conclude by highlighting the implications of these findings for the field of environmental social science.
Jun-Jun Jia et al 2024 Environ. Res. Commun. 6 061002
Figuring out household water demand response is of importance to sustainable water pricing policy making and optimalization. The paper estimates price and income elasticities of residential water demand in China by using the unique dataset from Chinese Household Water Use Behavior Survey 2019 in 50 cities. Two instrumental variables of marginal water price and average water price are used to address the endogeneity in the context of increasing-block water pricing policy. Results show that price elasticity ranges from −0.170 to −0.543, meaning that the demand for water is inelastic. Income elasticity ranges from 0.062 to 0.133, indicating that water is a necessary commodity. It unveils that water scarcity cities have more sensitive price response. It verifies the effectiveness of the differential increasing-block water pricing schemes tailor-made to local water resources endowments. Besides, it shows that high water-consuming households have more sensitive price response. It suggests that implementing more stringent IBWP scheme for those households constitutes a promising policy improvement option in the future.
Dayu Zhang et al 2024 Environ. Res. Commun. 6 061001
Hydrochlorofluorocarbons (HCFCs) are greenhouse gases and ozone-depleting substances, and existing HCFC emission studies lack a comprehensive study of multiple HCFCs in a single consumption sector. China is a large producer and consumer of HCFCs. The HCFC bank in foam sector in 2019 accounted for 91.3% of the national total, and foam sector was also the second largest source of HCFC emissions. Therefore, the estimation of HCFC emissions and banks for the foam sector is quite important. In this study, the multiple HCFC emission inventory for foam sector in eastern China from 2000 to 2019 was first established by using the bottom-up method. The results showed that the HCFC emissions and bank were 14.9 kt and 453.5 kt in 2019. HCFC-141b used in the polyurethane (PU) foam sector had the largest annual emissions, cumulative emissions, and bank due to its high consumption. The total emissions of HCFC-22 and HCFC-142b used in the extruded polystyrene (XPS) foam sector were similar to those of HCFC-141b. The HCFC emissions from the foam sector were mainly distributed among the three provinces of Jiangsu, Zhejiang, and Shandong. The cumulative GWP- and ODP-weighted emissions of HCFCs were 240.6 Mt CO2-eq and 14.3 kt CFC-11-eq, respectively. The results showed that in order to response to climate change or ozone depletion, we should prioritize the emission reduction of HCFC-22 and XPS foam sector, or HCFC-141b and PU foam sector.
Abdulaziz Aldegheishem 2024 Environ. Res. Commun. 6 055023
This study aims to assess the progress towards Sustainable Development Goal 11 (SDG 11) in Al-Madinah Al-Munawwarah, Saudi Arabia. The study also examines challenges that encounter SDG 11. To this end, six targets consisting of 40 indicators of SDG 11 have been adopted, relying on literature, international and national technical reports, and the personal perspectives of twelve experts. Overall progress towards SDG 11 has shown significant improvement considerably, with a middle level, particularly after Saudi Vision 2030 was approved. The findings show that three targets including affordable housing, sustainable transportation, and sustainable urbanization, have achieved average progress, and two targets, including air quality, and waste management, and access to green areas have been demonstrated low progress, as well as a single target, which is the preservation and protection of natural and cultural heritage, which has achieved optimal progress. The results highlight several challenges that hinder progress towards SDG 11, but the level of these challenges varies from one target to another target, ranging from moderate to major challenges. These challenges should be considered in continuing urban strategies and could be reduced by establishing resource-saving and innovative community urban renewal programs.
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Mengrong Shu et al 2024 Environ. Res. Commun. 6 052001
The original purpose of resilience design for traditional architectures is to be coordinated with and adapted to the natural environment. The natural environmental resilience of traditional dwellings refers to the ability of the dwellings to maintain the residents' comfort, safety, and health in the face of natural environmental challenges including various disasters. In the process of designing traditional dwellings, the wisdom contributed to improving living environment conditions is of significant reference value. Therefore, this paper reviews the main literature on the resilience of traditional dwellings to the natural environment in Fujian of China. A topical review framework is proposed to cover the resilience performance of traditional dwellings in Fujian under various natural environmental conditions. Specifically, it is divided into two aspects: internal comfort resilience and external disaster-resistance resilience, based on which researchers in related fields can establish a clearer classification of resilience research in their future studies. In terms of internal comfort resilience, this paper focuses on relevant perspectives such as humidity, temperature, brightness, noise, etc. In terms of external disaster-resistance resilience, this paper summarizes the adaptability of traditional dwellings in the face of disasters triggered by natural hazards such as fires, floods, earthquakes, and typhoons. Based on this framework, this paper reviews the current research status, discusses the limitations and shortcomings in this research area, and proposes corresponding prospects for future research.
Devi R Asih et al 2024 Environ. Res. Commun. 6 042001
Indonesia is renowned as an agricultural powerhouse, ranking first globally in oil palm production. This prominence in agriculture leads to the consistent generation of agro-industrial waste, notably Palm Oil Mill Effluent (POME). Effectively addressing these waste concerns is important due to their adverse impacts on aquatic ecosystems and the nation's health and economy. Anthropogenic wastewater with excessive phosphorus content can trigger eutrophication and toxic algal blooms, posing environmental risks and potentially precipitating a future clean water crisis. Thus, a comprehensive approach is necessary to restore the environment and biogeochemical cycles. Treatment efforts involving bioremediation agents aim to recycle organic and inorganic pollutants in the environment. Photosynthetic organisms like plants and microalgae serve as effective bioremediation agents, capable of absorbing excess phosphorus. They can utilize phosphate as an energy source to boost biomass. Integrating these bioremediation agents with bioengineering technology optimizes the treatment efficacy while simultaneously producing valuable biomass for products and bioenergy. This review article explores photosynthetic organisms' multifunctional role as phosphorus bioremediation agents for wastewater treatment, minimizing environmental pollutant impacts, and providing biomass for fertilizers, polymers, bioplastics, and renewable energy. Furthermore, this study unveils opportunities for future technological advancements in this field.
Dumisani Shoko Kori et al 2024 Environ. Res. Commun. 6 032002
Climate change adaptation research is currently a policy priority. For smallholder farmers, it provides opportunities for resilience building. The research area is growing rapidly and calls to synthesize existing data have been made. Existing work forms a basic picture of the trends in the research area. However, it is limited in scope and methodological approaches used. This work synthesizes climate change adaptation research on smallholder farmers in Southern Africa. It gives an overview of past and current directions of climate change adaptation research using a combination of bibliometric analysis techniques and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. Results show a steady growth in research, a disproportionate distribution of research and weak research collaboration among Southern African countries. Diverse methodologies are in use but a combination of approaches is rare. Co-occurrence of keywords show recognizable strides in research ranging from adaptation to mitigation linkages to the influence of climate change impacts on adaptation and livelihood outcomes. Strengthened research collaboration between countries in Southern Africa should be advocated for. This would help develop viable, appropriate and localized adaptation solutions. Equitable allocation of funding is pertinent to ensure uniform research activity and adaptation action across the region. A combination of research approaches is needed to push forward adaptation research on smallholder farmers in Southern Africa.
Coleman Vollrath et al 2024 Environ. Res. Commun. 6 032001
Research on methane (CH4) emissions from the oil and gas (O&G) industry informs policies, regulations, and international initiatives that target reductions. However, there has been little integration and synthesis of the literature to document the state of knowledge, identify gaps, and determine key insights that can guide research priorities and mitigation. To address this, we performed a scoping review of 237 English-language peer-reviewed articles on CH4 emissions from onshore O&G sources, charting data on five research themes: publication trends, geography, measurement levels and methods, emissions sources, and emissions rates. Almost all articles (98%) were published between 2012 and 2022 with an increasing publication rate, indicating a nascent and evolving understanding of the science. Most articles (72%) focused on CH4 emissions from the U.S. O&G industry and were written by U.S.-based authors (69%), while other major O&G-producing countries like Saudi Arabia, Russia, and China were under-represented. Upstream was the most frequently studied supply chain segment, where U.S.-focused articles accounted for 75% of the research. Nearly half the articles (43%) included in the review reported site-level measurements, limiting the identification of equipment- and component-level emissions sources and root cause. Articles that measured or identified equipment-level sources (18%) noted high emissions from tanks, unlit flares, and compressors. The most common stand-off measurement platforms were vehicles and aircraft, while the use of satellites increased in articles published since 2019. Reported emissions profiles were consistently heavy-tailed and indicate method-based and geographic differences in magnitude and skew. All articles (n = 26) that compared inventory- to measurement-based estimates of emissions found large discrepancies in that inventories under-estimated the latter by a factor of 1.2–10 times. We recommend future research focus on: (i) field-based emissions studies for under-represented regions and source categories, (ii) identifying root causes and linking measurements to mitigation, and (iii) multi-level measurement integration.
Haochuan Lin 2024 Environ. Res. Commun. 6 022002
Although traffic-related air pollution (TRAP) has been a long-standing problem, few bibliometric- and visual analysis-based literature reviews have been performed. In light of this issue, future research plans and directions in the field of TRAP must be determined. Therefore, this study performed a bibliometric analysis of the TRAP publishing trends, including the countries, institutional collaborations, author collaborations, keywords, and hotspots. The information visualization software CiteSpace was used to analyze the relevant literature collected from the Web of Science (WoS) from 2003 to 2022. The main findings of this study included the following: (1) the main keywords in TRAP research are particulate matter, exposure, health, nitrogen dioxide, and mortality; (2) current research is focused on the impacts of TRAP on humans; and (3) potential hotspots for future TRAP research are source apportionment, asthma, heart rate variability, and mobile monitoring. This article aims to develop a better understanding of current research trends in TRAP and provide directions for future research.
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Edgeley et al
Wildfires can rapidly generate post-fire flood risk for downslope communities, complicating recovery and necessitating accelerated cross-boundary responses on both public and private lands. Flood insurance is one of a suite of efforts to minimize the social and financial impacts associated with post-fire flood events, but little is known about who purchases coverage after wildfires or their experiences with that policy. We provide an opportunistic contribution to this research gap by comparing data gathered via three mixed-mode household surveys conducted in areas with modeled flood risk after two wildfires in the greater Flagstaff, Arizona area. Two surveys were administered – one in 2011 and one in 2020 – after the 2010 Schultz Fire, which resulted in significant flooding, providing a longitudinal insight into insurance experiences. A third survey was administered in 2022 following flooding adjacent to the 2019 Museum Fire. Together, these surveys resulted in a total of 1,351 usable responses. We find that several groups are significantly less likely to purchase flood insurance, including residents who moved to their property after the studied fire event and renters. The reported cost of flood insurance among households affected by the Schultz Fire doubled over a 10-year period; those who no longer maintained coverage typically reported that they stopped renewing between 2-5 years after the fire. Second homeowners were more likely to report damages that were not covered by insurance. We provide recommendations for engaging residents in uptake, renewal, and use of flood insurance and conclude that there is an urgent need to better understand decision-making surrounding post-fire flood insurance to support more equitable recovery.
Karpagam et al
Water is crucial to human survival in general, and determining the WQI (water quality index) is one of the primary aspects. The existing water quality classification models are facing various challenges and gaps that are impeding their effectiveness. These challenges include limited data availability, the intricate nature of water systems, spatial and temporal variability, non-linear relationships, sensor noise, and error, interpretability, and explainability. It is imperative to address these challenges to improve the accuracy and efficacy of the models and to ensure that they continue to serve as reliable tools for monitoring and safeguarding water quality. To solve the issues, this paper proposes a Stacked Ensemble efficient long short-term memory (StackEL) model for an efficient water quality index classification. At first, the raw input data is pre-processed to rescale the input data using data normalization and one-hot encoding. After that, the process known as variational mode decomposition (VMD) is applied to get at the intrinsic mode functions (IMFs). Consequently, feature selection is performed using an extended coati optimization (EX-CoA) algorithm to select the most significant attributes from the feature selection. Here, publicly available datasets, namely the water quality dataset from Kaggle, are used for classification and performed using are used to perform the Stacked Ensemble efficient long short-term memory (StackEL) classification process effectively. To further perfect the proposed prediction model, the Dwarf Mongoose optimization (DMO) method is implemented. Several measures of effectiveness are examined. When compared to other existing models, the suggested model can achieve a high accuracy of 98.85% of the water quality dataset.
Vincent M et al
Agroforestry is indeed a traditional practice followed in tropical
countries like India. About 28.43 million hectare area is used for agroforest
cultivation. By 2050 India has the mission of increasing the area under
agroforestry to 53 million hectares. In this study, we have made an effort to map
the agroforest areas using the geospatial tools and hybrid deep learning techniques.
The land utilized for cultivation and various agroforestry activities such as rubber,
tea, coconut, and banana plantation were classified as forest canopy by the existing
classifiers taking the tree canopy density as a parameter. In light of proposing
a solution to the issue, we have put forth a multi temporal hybrid deep learning
framework which is a fusion of convolutional neural network, a deep neural net
and long short term memory network to classify agroforestry distinguishing it
from the forest canopy using remote sensing data. The experimentation was
carried out in the southern districts of India, and Landsat 8 imagery was used to
classify the agroforestry of the study area that includes tea, banana, rubber,
coconut, and crop lands. An efficient multi temporal hybrid deep learning
framework was designed to classify the agroforest plantation distinguishing it
from crop lands and forest clusters. The experimental results of multi temporal
hybrid CNN+LSTM outperformed CNN, LSTM, BiLSTM model reducing the
error rate with respective accuracy and kappa score of 98.23% and 0.88. The
proposed method provides a benchmark to accurately classify and estimate the
LULC, particularly mapping the agroforest plantation for other regions across the
country.
Baldantoni et al
Anthropogenic activities, mainly in the form of local fuel exhausts and inputs from the coastline, heavily affect ecosystems at the interface between terrestrial and marine realms, impairing their functionality and the services they provide. Due to the central role of primary producers in trophic webs, their sessile nature and ethical concerns implied in experiments on animals, pollutant analyses in both sediments and macrophytes assume special relevance in assessing pollutant transfers from the abiotic to biotic compartments and their possible transfer through trophic webs. With a view to clarify the accumulation of inorganic and organic pollutants deriving from fuel exhausts on primary producers, the concentrations of Cu, Fe, Zn, phenanthrene and benzo[a]pyrene were determined in sediments and macrophytes collected from sites along the Cilento coast, in western Mediterranean Sea, characterized by different levels of anthropogenic pressures. The 18 species analysed, belonging to Cyanobacteria, Chlorophyta, Rhodophyta, Heterokontophyta and Embryophyta, exhibited different accumulation capabilities toward pollutants, with average concentrations of Cu, phenanthrene and benzo[a]pyrene in all the divisions (17.6±2.3 µg g-1 d.w., 34.3±2.1 ng g-1 d.w., 61.5±9.4 ng g-1 d.w., respectively) higher than those measured in sediments (4.0±0.7 µg g-1 d.w., 11.6±0.9 ng g-1 d.w., 14.8±1.0 ng g-1 d.w., respectively) and more than one order of magnitude higher in Embryophyta for Cu (62.9±7.1 µg g-1 d.w.) and in Cyanobacteria for benzo[a]pyrene (181±2 ng g-1 d.w.). The obtained findings constitute a reference for the accumulation capabilities of different taxa and for the behaviour of different fuel exhaust pollutants in marine coastal environments, with implication for their transfer across trophic webs.
Adimassu et al
Ethiopia's diverse agroecological zones showcase a variety of Climate Smart Agricultural (CSA) Practices, yet the documentation and prioritization of best-bet practices have been lacking. To address this gap, this study utilized the Climate Change, Agriculture, and Food Security (CCAFS)-CSA Prioritization framework. This approach was deployed across nine key agro-ecologies in Ethiopia to identify and prioritize CSA practices based on the three pillars of CSA and gender-equity considerations. By employing this participatory framework, this study successfully identified and prioritized over 200 Climate Smart Agricultural (CSA) practices within Ethiopia's nine major agroecological zones. These practices were segmented into four main systems: crop management (40 practices), livestock management (41 practices), soil fertility management (40 practices), erosion control and water management (41 practices), and forest and agroforestry (40 practices). Notably, the results highlighted the significance of CSA practices linked to agroforestry/forestry management, rangeland/forage enhancement, exclosure strategies, and water management in addressing the goals associated with the three pillars (productivity, adaptation, mitigation) of CSA practices simultaneously. The findings also revealed that the majority of Climate Smart Agricultural (CSA) practices focused on improving productivity and enhancing adaptation to climate change. Additionally, the results demonstrated that trade-offs exist among the three pillars of CSA, emphasizing the need for integration with other practices to enhance complementarity and achieve all pillars simultaneously. Overall, this study underscores the importance of combining CSA practices of various categories to maximize their effectiveness and impact in sustainable agriculture