Land use is a critical factor in the siting of renewable energy facilities and is often scrutinized due to perceived conflicts with other land demands. Meanwhile, substantial areas are devoted to activities such as golf, which are accessible to only a select few and have a significant land and environmental footprint. Our study shows that in countries such as the United States and the United Kingdom, far more land is allocated to golf courses than to renewable energy facilities. Areas equivalent to those currently used for golf could support the installation of up to 842 GW of solar and 659 GW of wind capacity in the top ten countries with the most golf courses. In many of these countries, this potential exceeds both current installed capacity and medium-term projections. These findings underscore the untapped potential of rethinking land use priorities to accelerate the transition to renewable energy.

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.

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.

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.

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.

In Washington, Oregon, and California, ignitions from recreational activities accounted for 12% of human-caused wildfires, and 8% of the area burned, from 1992–2020. Wildfires ignited by recreational activities not only increase fire suppression expenditures but have the potential to limit recreational activities traditionally associated with use of fire, such as camping. From 1992–2020, 50% of recreation-caused ignitions in these three states occurred on lands managed by the U.S. Forest Service. The mean annual number of recreation-caused ignitions on national forests in the three states during this period was relatively stable, about 500, whereas recreation-caused ignitions within other jurisdictions decreased by 40%. Improved understanding of the impact of human and climatic factors on recreation-caused ignitions could provide valuable insights for shaping policy and management decisions. We found that mean annual densities of recreation-caused ignitions on national forests were 7 times greater within 1 km of designated campgrounds than >1 km from campgrounds, although 80% of recreation-caused ignitions occured >1 km from designated campgrounds. Ignition density in campgrounds increased non-linearly with overnight visitor density; a doubling of visitor density was associated with a ∼40% increase in ignitions. Large (≥4 ha) recreation-caused wildfires, especially those ignited in designated campgrounds, tended to occur concurrent with drought and 1–2 years after anomalously wet conditions. These results suggest that accounting for drought in implementation of fire restrictions, and targeting wildfire-prevention awareness to recreational users outside designated campgrounds, might reduce the likelihood of recreation-caused ignitions.

Achieving the Sustainable Development Goals (SDGs) remains a significant challenge for many countries, particularly in the face of increasing environmental pollution. Balancing social, economic, and environmental sustainability under these conditions is especially complex. This study explores the role of green finance in promoting sustainable infrastructure, innovation in green technology, corporate social responsibility, economic stability, and environmental conservation within the framework of Belt and Road initiative (BRI), with a specific focus on the China-Pakistan Economic Corridor (CPEC) initiatives. Furthermore, the study examines the role of government support in facilitating the issuance of GF, emphasizing its significance in large-scale international development projects like CPEC. Data were collected through a structured questionnaire targeting a diverse group of respondents, including businessmen, CPEC officials, and representatives from the Ministry of Finance, Pakistan Environmental Protection Agency, and Ministry of Planning and Development. Partial Least Squares analysis was employed to test the proposed relationships and hypotheses. The results indicate a significant positive impact of green finance on the development of sustainable infrastructure and the innovation of green technology. Additionally, the results underscore the pivotal role of environmentally friendly technologies and sustainable infrastructure in driving the achievement of SDGs, especially in the social, economic, and environmental dimensions. The study findings offer actionable insights for policymakers, highlighting the critical need to integrate green finance with sustainable practices to foster economic growth and environmental protection. These findings provide a strategic roadmap for nations aiming to align their development goals with global sustainability standards.

Company transition plans toward a low-carbon economy are key for effective capital allocation and risk management. This paper proposes a set of 64 indicators to comprehensively assess transition plans and develops a Large Language Model-based tool to automate the assessment of company disclosures. We evaluate our tool with experts from 26 institutions, including financial regulators, investors, and non-governmental organizations. We apply the tool to the sustainability reports from carbon-intensive Climate Action 100+ companies. Our results show that companies tend to disclose more information related to target setting (talk), but less information related to the concrete implementation of strategies (walk). In addition, companies that disclose more information tend to have lower emissions. Our results highlight the need for increased scrutiny of companies' efforts and potential greenwashing risks. The complexity of transition activities presents a major challenge for comprehensive large-scale assessments. As shown in this paper, novel and flexible approaches using Large Language Models can serve as a remedy.

Arctic areas store vast soil carbon reserves that are highly sensitive to be released into the atmosphere due to a warming climate. Large arctic herbivores may shape this sensitivity, but owing to high spatial and temporal variation in their ecosystem effects, the conditions under which herbivores might negate soil carbon losses have remained elusive. Here, we summarize the main pathways by which ungulates may counteract unwanted climatic feedbacks of the ongoing warming. Firstly, they may counteract the climate-induced shrubification; secondly, induce ecosystem state transitions from shrub and moss dominance to grass and forb dominance; and thirdly, contribute to colder winter soil temperatures. In non-permafrost soils, these pathways feed back on climate mostly via herbivory-induced increases in albedo and, potentially, decreased sensitivity to wildfire-induced soil carbon losses. In permafrost soils, herbivores may additionally enhance soil carbon storage as the colder winter soil temperatures, induced by vegetation change and trampling-associated compaction of snow, may prevent permafrost melting under warming. The role of current large animal populations in the first pathway (i.e., counteracted shrubification) is already documented in many parts of the Arctic. Yet, the second and third pathway (i.e., ecosystem state transitions and snow-mediated permafrost feedbacks have only limited occurrence today and would require drastic increases in the number and diversity of herbivores to change arctic climate feedbacks at a larger scale, imposing a high degree of uncertainty on the feasibility of such efforts. Given the alarming trends the arctic carbon stocks are facing, a better understanding of the contribution of large herbivores to the carbon cycle is more urgent than ever before, relevant if introducing animal populations into areas with large carbon reservoirs, and crucial when evaluating the net effect of current animal populations that already counteract shrubification and the warming-induced increase in albedo in many areas.

Machine learning and deep learning models have become essential in the recent fast development of artificial intelligence in many sectors of the society. It is now widely acknowledge that the development of these models has an environmental cost that has been analyzed in many studies. Several online and software tools have been developed to track energy consumption while training machine learning models. In this paper, we propose a comprehensive introduction and comparison of these tools for AI practitioners wishing to start estimating the environmental impact of their work. We review the specific vocabulary, the technical requirements for each tool. We compare the energy consumption estimated by each tool on two deep neural networks for image processing and on different types of servers. From these experiments, we provide some advice for better choosing the right tool and infrastructure.

Urban dynamics, especially in emerging nations, pose major challenges due to rapid population growth, economic development, and technology breakthroughs. Climate change, natural catastrophes, and socioeconomic inequality all pose difficulties to resilient housing globally, but in Pakistan, these problems are exacerbated by the country's fast urbanization, informal settlements, and governance shortcomings. The increasing demands further exacerbate the issue, highlighting the urgent need for climate-resilient solutions, especially for housing. Achieving Sustainable Development Goals requires pursuing climate-resilient housing that can withstand extreme weather conditions such as intense heat waves, urban flooding, and severe storms. The present study investigates the climatic vulnerabilities in Pakistan that create significant environmental, social, and economic stress. The study identifies key vulnerabilities in selected case studies through post-occupancy evaluation, focus group discussion, and in-depth interviews. A systematic table of indicators for physical, social, and economic resilience is also proposed to improve the overall quality of the housing sector. This study's results demonstrate that incorporating various identified indicators can reduce climate vulnerabilities in the housing sector. Additionally, the post-occupancy evaluation of case studies verified that integrating innovative construction techniques and materials in resilient houses reduced indoor temperature by 5–8 °C and provided better flood resilience by 25–30% compared to neighboring houses in the same context. The results of this research contribute to the process of strengthening housing against climate change challenges in an efficient and timely manner, taking into account the aspects of both resilience and sustainability.

Rampant industrial growth and urbanization have caused a wide range of hazardous contaminants to be released into the environment resulting in several environmental issues that could eventually lead to ecological disasters. The unscientific disposal of urban and industrial wastes is a critical issue as it can cause soil contamination, bioaccumulation in crops, groundwater contamination, and changes in soil characteristics. This article explores the impact of various industrial and urban wastes, including petroleum hydrocarbons (PHs), coal-fired fly ash, municipal solid waste (MSW) and wastewater (MWW), and biomedical waste (BMW) on various types of soil. The contamination and impact of each of these wastes on soil properties such as compaction characteristics, plasticity, permeability, consolidation characteristics, strength characteristics, pH, salinity, etc is studied in detail. Most of the studies indicate that these wastes contain heavy metals, organics, and other hazardous compounds. When applied to the soil, PHs tend to cause large settlements and reduction in plasticity, while the effect of coal-fired fly ash varies as it mainly depends on the type of soil. From the studies it was seen that the long-term application of MWW improves the soil health and properties for agricultural purposes. Significant soil settlements were observed in areas of MSW disposal, and studies show that MSW leachate also alters soil properties. While the impacts of direct BMW disposal have not been extensively studied, few researchers have concentrated on utilizing certain components of BMW, like face masks and nitrile gloves to enhance the geotechnical characteristics of weak soil. Soil remediation is required to mitigate the contamination caused by heavy metals and PHs from these wates to improve the soil quality for engineering and agricultural purposes, avert bioaccumulation in crops, and pose less environmental and public risks, and ecotoxicity. Coal-fired fly ash and biomedical waste ash contain compounds that promote pozzolanic reactions in soil, recycling and reuse as soil stabilizers offer an effective strategy for their reduction in the environment, thus complying to sustainable practices. In essence, this study offers a contemporary information on the above aspects by identifying the gaps for future research and mitigation strategies of contaminated soils.

This study investigates the spatiotemporal variation of nitrogen (N) and phosphorus (P) nutrient concentrations across diverse ecological within a 'river-reservoir' hydrological overlapping system. Using monthly monitoring data of total nitrogen (TN), total phosphorus (TP), ammonia nitrogen (NH₃-N), and permanganate index (COD_Mn) collected from designated monitoring stations along the Liuchong River and the upper reaches of Wujiang River between 2020 and 2023, this study aims to understand the primary drivers and influencing mechanisms behind the observed variations in N and P concentrations. The findings revealed that from 2020 to 2023, the TP concentration exhibited a consistent decline, while the TN, NH₃-N, and COD_Mn concentrations displayed nonlinear fluctuations in both the river and reservoir sections. The average nitrogen-to-phosphorus (N/P) ratio frequently exceeded 55, indicating phosphorus limitation within water bodies. The reservoir areas demonstrated a retention effect on N and P, with TP retention rates exceeding those of TN. This differential retention significantly increases the risk of eutrophication in reservoir waters. Rainfall-induced runoff variations were identified as the primary driver of N and P distribution, while retention effects and internal loading functioned as dual regulatory factors influencing the nutrient cycling dynamics within the reservoir. This study elucidates the influence and underlying mechanisms of the river-reservoir overlapping system on the spatial and temporal distribution of N and P in water bodies. The findings offer a scientific basis for safeguarding groundwater ecosystems, particularly in the context of cascade reservoir construction in the Wujiang River basin.

This study focuses on the impact of climate intervention under the ARISE-SAI-1.5 scenario of stratospheric aerosol injection (SAI) on projected malaria distribution in South Asia, relative to climate change under the SSP2-4.5 scenario, during the period 2045 to 2069. A dynamic malaria model is employed to assess the impacts of SAI and climate change on malaria redistribution. In addition to the entomological inoculation rate (EIR), the length of the transmission season (LTS) and malaria cases are considered as quantitative indicators of malaria transmission. The quantification of the projected malaria distribution employing several statistical techniques, including the probability density function technique, enables the assessment of malaria variability and risk across all seven highly climate-vulnerable countries of South Asia (Afghanistan, India, Iran, Bangladesh, Bhutan, Nepal, and Pakistan). Due to the lower temperatures achievable under ARISE-SAI-1.5 scenario relative to SSP2-4.5 scenario, the frequency of EIR occurrence shifts toward lower intensity values. This decrease in EIR is more pronounced in populous India and Bangladesh than in the other five South Asian countries during 2045–2069. The projected magnitude of LTS and the frequency of malaria case occurrences also diminish under ARISE-SAI-1.5 in South Asia.

The impact of floods may be exacerbated due to urban sprawl, which leads to residential development in naturally flood-prone areas. In the United States (US), urban sprawl has been historically tied to racial segregation, while flood-prone suburban development has been facilitated by flood insurance. While previous studies have found links between flood exposure and socio-demographic inequities, no research has addressed this question by looking at watershed-level segregation and the location of properties relative to flood-prone areas. We evaluate socio-demographic patterns of flood impact during the 2016 Floods in Louisiana (LA), USA, and whether these impacts differed inside or outside the FEMA Special Flood Hazard Area (SFHA), the nation's main flood risk indicator for property owners. We assess this question in the Amite River Basin (ARB), LA, looking at the following socio-demographic predictors: (1) race, (2) income, (3) year of property built, and (4) property type, and accounting for the location of properties relative to the FEMA-SFHA (inside/outside), and the Parish of origin. The FEMA SFHA was generally a good predictor of flood impact, and the most impacted parishes were those within the downstream area of the ARB (EBR-East Baton Rouge, Ascension, and Livingston). At the watershed scale, properties in blocks dominated by wealthier black residents had a greater impact during this flood event, but the trends, varied by parish. Trends in the older and more urban EBR parish reflected those reported for the watershed. In the newer suburban parishes of Ascension and Livingston, the highest impact was experienced by high-income, predominantly white neighborhoods, mainly inside the FEMA SFHA. Properties built between 1970–1989 were associated with higher flood impact than homes built during other periods. While socio-demographic predictors of flood exposure were heterogeneous across the ARB, our findings collectively highlight the social costs of suburbanization into hazardous areas.

Rampant industrial growth and urbanization have caused a wide range of hazardous contaminants to be released into the environment resulting in several environmental issues that could eventually lead to ecological disasters. The unscientific disposal of urban and industrial wastes is a critical issue as it can cause soil contamination, bioaccumulation in crops, groundwater contamination, and changes in soil characteristics. This article explores the impact of various industrial and urban wastes, including petroleum hydrocarbons (PHs), coal-fired fly ash, municipal solid waste (MSW) and wastewater (MWW), and biomedical waste (BMW) on various types of soil. The contamination and impact of each of these wastes on soil properties such as compaction characteristics, plasticity, permeability, consolidation characteristics, strength characteristics, pH, salinity, etc is studied in detail. Most of the studies indicate that these wastes contain heavy metals, organics, and other hazardous compounds. When applied to the soil, PHs tend to cause large settlements and reduction in plasticity, while the effect of coal-fired fly ash varies as it mainly depends on the type of soil. From the studies it was seen that the long-term application of MWW improves the soil health and properties for agricultural purposes. Significant soil settlements were observed in areas of MSW disposal, and studies show that MSW leachate also alters soil properties. While the impacts of direct BMW disposal have not been extensively studied, few researchers have concentrated on utilizing certain components of BMW, like face masks and nitrile gloves to enhance the geotechnical characteristics of weak soil. Soil remediation is required to mitigate the contamination caused by heavy metals and PHs from these wates to improve the soil quality for engineering and agricultural purposes, avert bioaccumulation in crops, and pose less environmental and public risks, and ecotoxicity. Coal-fired fly ash and biomedical waste ash contain compounds that promote pozzolanic reactions in soil, recycling and reuse as soil stabilizers offer an effective strategy for their reduction in the environment, thus complying to sustainable practices. In essence, this study offers a contemporary information on the above aspects by identifying the gaps for future research and mitigation strategies of contaminated soils.

Sustainable lifestyle changes are an important demand-side solution to reducing CO₂ emissions. While sustainable lifestyles are increasingly included in integrated assessment models, modellers have so far not managed to realistically model what drives changes in lifestyles. Important questions about the feasibility and likelihood of lifestyle change, and how lifestyle changes can be accelerated or promoted thus go unanswered. Environmental psychology is a discipline dedicated to understanding environmental behaviour, and its theories and findings could therefore be instrumental to informing the modelling of lifestyle change in integrated assessment models. Yet, we identify two barriers currently hindering the systematic integration of this knowledge into integrated assessment modelling. The first barrier is plurality: there are many theories and findings that are potentially relevant to modelling lifestyle change, but guidance is lacking on which to apply when. The second barrier is ambiguity: many theories in psychology are not precise enough to unambiguously translate them into a mathematical model. To overcome the barrier of plurality, we introduce the Motivation, Agency, and Past behaviour (MAP) framework, which summarises and integrates the insights of 8 prominent behavioural theories used in environmental psychology and that can be used to determine which theories and determinants are most relevant for specific modelling applications. To overcome the barrier of ambiguity, we identify three areas where the precision of theorizing in environmental psychology can be improved, namely definitions and consistent use of constructs, the specification of relationships between constructs, and describing the strength and boundary conditions of these relationships. We urge for closer collaborations between modellers and environmental psychologists to successfully model the drivers and impacts of sustainable lifestyle change.

This systematic review uniquely explores the impact of carbon reduction measures on human comfort from a human factors and ergonomics perspective, focusing on human comfort. An analysis of 30 papers identifies key environmental factors requiring attention in contemporary carbon reduction strategies and their implications for human comfort. The results reveal a growing emphasis on thermal comfort and air quality in carbon reduction retrofits, while other environmental factors such as light and noise receive insufficient attention. While optimal ventilation and local environmental adjustments can yield positive outcomes, adverse effects like significant indoor temperature fluctuations and heightened carbon dioxide levels may arise from certain modifications. Moreover, the findings from the analysis of human comfort assessment methods indicate a lack of focus on human comfort evaluation in carbon emission reduction initiatives, with predominant reliance on subjective questionnaires. Most studies superficially mention human comfort assessment without delving into comprehensive research or employing systematic evaluation techniques. The findings indicate that although the implementation of carbon reduction measures is extensively covered in academic literature, the limited literature addressing human comfort assessment post-implementation implies a need for further comprehensive exploration and development within the field. This study furnishes researchers, practitioners, and policymakers with a comprehensive insight into the current landscape and proposes prospective research avenues within the domain.

Arctic areas store vast soil carbon reserves that are highly sensitive to be released into the atmosphere due to a warming climate. Large arctic herbivores may shape this sensitivity, but owing to high spatial and temporal variation in their ecosystem effects, the conditions under which herbivores might negate soil carbon losses have remained elusive. Here, we summarize the main pathways by which ungulates may counteract unwanted climatic feedbacks of the ongoing warming. Firstly, they may counteract the climate-induced shrubification; secondly, induce ecosystem state transitions from shrub and moss dominance to grass and forb dominance; and thirdly, contribute to colder winter soil temperatures. In non-permafrost soils, these pathways feed back on climate mostly via herbivory-induced increases in albedo and, potentially, decreased sensitivity to wildfire-induced soil carbon losses. In permafrost soils, herbivores may additionally enhance soil carbon storage as the colder winter soil temperatures, induced by vegetation change and trampling-associated compaction of snow, may prevent permafrost melting under warming. The role of current large animal populations in the first pathway (i.e., counteracted shrubification) is already documented in many parts of the Arctic. Yet, the second and third pathway (i.e., ecosystem state transitions and snow-mediated permafrost feedbacks have only limited occurrence today and would require drastic increases in the number and diversity of herbivores to change arctic climate feedbacks at a larger scale, imposing a high degree of uncertainty on the feasibility of such efforts. Given the alarming trends the arctic carbon stocks are facing, a better understanding of the contribution of large herbivores to the carbon cycle is more urgent than ever before, relevant if introducing animal populations into areas with large carbon reservoirs, and crucial when evaluating the net effect of current animal populations that already counteract shrubification and the warming-induced increase in albedo in many areas.

Achieving global carbon neutrality by 2050 requires substantial decarbonization of the built environment, with LCA playing a critical role in evaluating buildings' environmental impacts. Among the primary LCA methodologies, CLCA offers unique decision-support capabilities but faces limited adoption in the building sector, restricting its effectiveness. This study investigates the methodological challenges contributing to the low adoption of CLCA, focusing on issues such as goal and scope definition, consequential life cycle inventory (CLCI) modelling, and uncertainty analysis. A systematic review of 20 building-related CLCA studies was conducted using an adapted CLCA framework based on the step-wise process by Weidema et al (2009). Studies with strong alignment to the framework provided robust insights into decision contexts, market dynamics, co-products, and uncertainty analysis, enhancing transparency and replicability. Conversely, studies with significant gaps struggled with poorly defined decision contexts, insufficient data, and the omission of uncertainty analyses, reducing their reliability and applicability. This review underscores the growing potential of CLCA in sustainability assessments within the built environment. However, technological constraints, data limitations, and methodological complexities hinder its broader adoption and comparability. A tailored CLCA framework for the construction sector is proposed to address these gaps, incorporating decision trees, standardized templates, and uncertainty analysis guidelines to improve transparency, robustness, and decision-making support in achieving a low-carbon built environment.

Ammonia (NH₃) volatilization and nitrate leaching contribute to major losses of reactive nitrogen (Nr) in agriculture, leading to global environmental concerns. Effective measures are needed to mitigate Nr losses and improve nitrogen (N)-use efficiency in agricultural practices. This study, conducted in farmers' fields in Shewaki near Kabul City, Afghanistan, during the 2021 spring season, sought to address Nr-losses in agriculture. Nine treatments were organized into three categories: (A) animal manure + chemical fertilizer, (B) night soil + chemical fertilizer, and (C) chemical fertilizer alone, along with an unamended control. Chemical fertilizer and manure were applied at varying rates (±25% and a recommended rate) using both surface and sub-surface application methods. Sub-surface application reduced NH₃ emissions by 55% compared to surface application. Treatment group 'A' had a 32% NH₃ loss, while the unamended control (receiving N from irrigation water and dust only) showed a 13% loss. For nitrate leaching, group 'B' showed the highest loss, followed by group 'C'. Overall, agronomic practices reduced N-losses significantly, resulting in a net positive N-balance. Nuse efficiency was highest in group 'C' at 130%, followed by groups 'B' and 'A'. The findings suggest that sub-surface application techniques are effective in reducing N-losses and enhancing N-use efficiency, and highlight the potential to improve nutrient use efficiency by adjusting fertilizer and manure inputs in similar agricultural systems.

Politically influenceable factors are considered to be the most important predictors of acceptability of 
restrictive transport policy measures, also known as push measures. Policymakers can therefore ac tively influence the acceptability of measures through the design of measures. Nevertheless, in prac tice, policymakers often refrain from implementing push measures due to the supposedly low accepta bility of push measures among the population. This paper therefore examines the question of how 
transport policy push measures can be made more acceptable through their specific design. This is in tended to contribute to a better understanding of the acceptability of measures and to show policymak ers how they can implement push measures. For this purpose, a quota-representative quantitative 
online survey (n=1,100) of the urban population of Germany was carried out. In this survey, various 
features of four different push measures were surveyed – parking fee increases, redistribution of street 
space, access restrictions and a 30 km/h speed limit. The results of the survey demonstrate that there is 
already a high level of acceptability for some of the measures. It also becomes clear that more disrup tive features lead to greater rejection and non-traffic uses are viewed positively. Furthermore, it can be 
stated, that large parts of urban society are already open to more disruptive designs of push measures. 
Policymakers can therefore actively influence the level of acceptability of push measures among the 
population. Policymakers should act flexible and integrated when developing measures and know the 
needs of the population in order to be able to develop acceptable and effective measures. The results of 
this study contribute to a more precise understanding of the acceptability of push measures and at the 
same time show how policymakers can implement even controversial push measures.

With the development of the coal mine industry, the treatment of domestic sewage in coal mines has become an essential topic of environmental protection. Traditional sewage treatment methods have problems such as low efficiency and complicated management, and it is challenging to meet the increasingly strict environmental protection requirements. Therefore, the research of intelligent dosing and control systems becomes necessary. Based on the STM32F303 microcontroller, this study designs and implements an intelligent dosing and control analysis system for coal mine domestic sewage. The system monitors critical parameters such as pH value, turbidity, and dissolved oxygen in sewage in real time and adopts a fuzzy control algorithm and Proportional-Integral-Derivative Control Algorithm (PID) control strategy to realize intelligent adjustment of the dosing process. Through experimental verification, the system can effectively reduce Chemical Oxygen Demand (COD) and Biochemical Oxygen Demand (BOD) in sewage under different pollution load conditions, improve treatment efficiency, and ensure the sewage effluent quality meets the national discharge standard. The experimental data show that the control error of the system is less than ± 2%, the dosing accuracy is more than 10% higher than that of the traditional system, the degree of automation is significantly improved, and the operation is convenient.

The source region of the Yellow River is an important ecological barrier of the Qinghai-Tibet Plateau in China. In recent decades, the ecological environment in the source region of the Yellow River has been deteriorating continuously, which not only endangers the living environment of the region, but also seriously hinders the sustainable development of regional ecology, society and economy. At present, the interaction mechanism among land use, landscape pattern and driving factors in the source region of the Yellow River has not been revealed. Based on the remote sensing image data of the source region in the past 30 years, the evolution law of landscape pattern was analyzed by land transfer matrix and landscape pattern index, and the driving factors were explored by principal component analysis. The results showed that: (1) the rate of land use change in the source region was slow in recent 30 years, and the change of grassland and unused land area was the largest. (2) Grassland is the most dominant landscape type in the source region and has the best natural connectivity. The fragmentation of forest landscape is serious. The landscape patch density, maximum patch index, dispersal and juxtaposition index and Shannon diversity index in the source area showed a decreasing trend, while the girth to area ratio showed an increasing trend, indicating that the landscape types were more complex in shape. The land use structure in the source region of the Yellow River is more reasonable, the landscape pattern changes tend to be stable, and the ecological environment is gradually improved. (3) Social and economic factors were the main causes of landscape pattern change in the source region. This study can provide scientific basis for rational utilization of land resources, ecological protection and restoration in the source region of the Yellow River.

Vermicompost is a nutrient-rich organic fertilizer that contains macronutrients, micronutrients, beneficial soil microflora, and plant growth regulators. An experiment was conducted at the Vermiculture Center, College of Agriculture, Hawassa University, Ethiopia in 2023 to assess the impact of feedstock type on selected physicochemical properties and nutrient composition of vermicompost. Common bean straw, coffee husk, maize stalk, and enset leaves were used as feedstock materials individually and in various combinations. The feedstocks were mixed with cow dung at a 2:1 ratio based on dry weight and arranged in a completely randomized design. Each 30 kg feedstock in the worm bin was supplied with 500 grams of Eisenia fetida earthworms. Upon maturity, the vermicompost was harvested by removing earthworms and other materials through a 4-mm sieve. Results showed significant differences in the physicochemical properties of vermicompost derived from different feedstocks. Common bean straw + cow dung reached maturity the fastest (66 days), while maize stalks + cow dung took the longest (85 days). The combination of common bean straw + coffee husk + cow dung yielded the highest vermicompost output (13.8 kg), while the lowest output (10.8 kg) was obtained from enset leaves + cow dung. Organic carbon content decreased by 39-100% in vermicompost compared to the original feedstock, while total nitrogen content increased significantly by 59-157%. The study concluded that the common bean straw + coffee husk + cow dung combination produced vermicompost with the best physicochemical properties and nutrient composition, and hence recommended choice for vermicompost production.