The research team, led by Panithi Nakhonthong and Preenithi Aksorn of Khon Kaen University, examined the Nakhon Pathom–Nong Plalai section of the Nakhon Pathom–Hua Hin double-track railway project, a State Railway of Thailand undertaking spanning roughly 93 kilometres across three provinces with a construction budget of about 8.20 billion Thai baht. Using a process-based life cycle assessment (LCA) following the ISO 14040 and 14044 frameworks, they compiled a cradle-to-gate inventory covering raw material extraction, material production, transport to site, on-site construction, and equipment energy use. The functional unit was the construction of the entire 93-kilometre section, with results reported both as total emissions and as a normalized intensity per kilometre to allow comparison with international benchmarks.

The headline numbers are striking. Building the line generated approximately 0.27 megatonnes of carbon dioxide equivalent, or about 2,941 tonnes of CO2-equivalent per kilometre. Structural work—bridges, overpasses, and other reinforced concrete and steel elements—was the single largest hotspot, contributing 67.05 percent of the total, followed by track work at 19.75 percent, station work at 10.30 percent, and earthwork at just 2.90 percent. Within the material inventory, reinforcing steel alone contributed roughly 110,535 tonnes of CO2-equivalent, rails added nearly 49,000 tonnes, and cement more than 45,000 tonnes. Ballast, hauled in enormous quantities for the track bed, contributed about 29,378 tonnes. By contrast, all the diesel fuel burned by construction machinery—more than three million litres of off-road diesel—produced only about 8,300 tonnes.

These results echo a consistent pattern documented across transportation infrastructure worldwide. Chang and Kendall’s landmark assessment of California’s high-speed rail showed that material production dominated construction emissions, and subsequent studies of Korean and Chinese high-speed lines confirmed that bridges, rails, sleepers, and concrete structures are the principal hotspots. The Thai case extends this evidence to a conventional double-track railway delivered under local procurement and supply-chain conditions, using domestic emission factors from the Thailand Greenhouse Gas Management Organization and the Thai Life Cycle Inventory database, supplemented by the international Inventory of Carbon and Energy. The consistency across such different contexts suggests that embodied carbon in steel and cement is a universal challenge for infrastructure decarbonization, not a quirk of any single country’s construction practices.

One of the study’s most instructive comparisons involves emission intensity. The Thai line’s 2,941 tonnes of CO2-equivalent per kilometre sits far below the figures reported for high-speed railways, which range from about 3,310 to a staggering 32,790 tonnes per kilometre. But the researchers caution against reading this as evidence of superior environmental performance. The decisive variable is structural composition: the Thai conventional line has an estimated bridge share of only about 10 percent, whereas the high-speed benchmarks carry 15 to 75 percent of their length on elevated structures. Bridges demand vastly more concrete and steel, and therefore vastly more embodied carbon. Headline intensity figures, the authors argue, are meaningless without accounting for what a railway is actually made of—a lesson for any policymaker tempted to rank projects by a single number.

What distinguishes this study from earlier railway LCAs is not the hotspot identification itself but the bridge it builds from measurement to management. The researchers recognize that an LCA result, however precise, does not by itself determine who should act, whether an alternative is feasible, or when an intervention should occur. To address this, they conducted semi-structured interviews with 40 experienced stakeholders—project managers, engineers, inspectors, and technicians—directly involved in the project, eliciting their views on practical mitigation measures across five life-cycle stages, from initial design through post-construction evaluation. From the literature and field observations, the team synthesized thirteen environmental intervention factors, spanning appropriate design, low-carbon and recycled material selection, construction-method choice, local sourcing to shorten transport distances, equipment efficiency, monitoring, and post-project assessment.

The interviews revealed a clear pattern of perceived priority. Early-stage measures dominated: appropriate structural design ranked first with 115 quotations, followed closely by environmentally friendly or recycled material selection with 112, and construction-method selection with 101. Exploratory correlation analysis showed strong co-occurrence among these themes, with the strongest relationship—between appropriate design and green material selection—reaching a Pearson coefficient of 0.9098. Construction-stage measures such as machine efficiency and green technology innovation, along with post-construction equipment management, attracted far less attention. The researchers are careful to stress that quotation frequency reflects perceived priority within this sample, not measured carbon savings or population-wide agreement.

The methodological heart of the paper is an intervention-screening matrix that cross-classifies LCA hotspot magnitude against stakeholder priority, assigning each combination a distinct next step. Measures that are both environmentally significant and strongly supported—such as steel- and cement-efficient structural design or lower-carbon material options—proceed immediately to quantitative LCA scenario testing and engineering feasibility assessment, and may be adopted only if a net greenhouse gas reduction is demonstrated. High-emission inputs that lack implementation support trigger a barrier, responsibility, and supply review before any scenario analysis, with the explicit rule that a measured hotspot must not be deprioritized simply because stakeholders mentioned it less often. Conversely, actions that stakeholders rate highly but which touch only minor emission flows—equipment upgrades, training, monitoring—require verification of their actual environmental leverage before any savings can be claimed. Low-priority items on both dimensions remain under periodic monitoring. This decision logic preserves the independence of the two evidence streams while preventing either from masquerading as the other.

A one-way sensitivity analysis reinforced the robustness of the core conclusions. Varying the combined reinforcing and structural steel emission factor by plus or minus 20 percent produced the largest absolute response—a 20 percent increase raising the total by roughly 31,811 tonnes of CO2-equivalent—while cement quantity changes of plus or minus 10 percent and a 50 percent proportional variation in ballast-related transport activity had smaller effects. Crucially, across all tested ranges, structural work remained the largest work-category hotspot, meaning the prioritization conclusion held even as the magnitude of the estimate shifted. The authors acknowledge limitations: the cradle-to-gate boundary excludes operation, maintenance, and end-of-life phases; the analysis rests on a single Thai project; and the deterministic stress tests provide directional sensitivity rather than statistical confidence intervals.

The practical implications reach well beyond one railway. For designers, the message is that structural optimization and material-efficient engineering offer the greatest carbon leverage, particularly for bridges and elevated structures. For contractors, the findings suggest that waste reduction, logistics planning, and rework minimization matter mainly because they curb demand for carbon-intensive materials rather than because of fuel savings. For project owners and policymakers, the framework offers a template for embedding life cycle thinking into procurement: require a baseline LCA, identify material hotspots, apply the screening matrix, and commission comparative scenarios for technical alternatives before contracts are signed. The authors emphasize that the numerical priorities cannot simply be transferred to other countries or infrastructure types—each application demands a new local inventory, context-specific thresholds, and fresh feasibility checks. But the underlying logic, that measured environmental significance and stakeholder feasibility must be kept distinct and then deliberately combined, offers a transparent and reproducible pathway for any material-intensive infrastructure project seeking genuine, verifiable carbon reductions rather than well-intentioned gestures.

Subject of Research: Life cycle assessment of greenhouse gas emissions from conventional double-track railway construction in Thailand and stakeholder-informed screening of low-carbon management responses

Article Title: Environmental challenges of railway infrastructure: linking life cycle assessment with management responses for low-carbon construction

Article References: Nakhonthong, P., & Aksorn, P. (2026). Environmental challenges of railway infrastructure: linking life cycle assessment with management responses for low-carbon construction. Environmental Challenges, 25, Article 101660. https://doi.org/10.1016/j.envc.2026.101660

Image Credits: AI Generated

DOI: 10.1016/j.envc.2026.101660

Keywords: railway infrastructure, life cycle assessment, embodied carbon, greenhouse gas emissions, steel and cement, sustainable construction, Thailand, double-track railway, stakeholder interviews, low-carbon materials, procurement, carbon footprint

The problem the researchers set out to solve is a paradox familiar to environmental agencies across Europe. Everyone agrees that recreation can harm freshwater life, yet under the European Water Framework Directive, recreational activities are not even recognised as a distinct pressure category. Their effects get folded invisibly into broader categories such as hydromorphological alteration or biological disturbance, which means they are routinely underrepresented in official pressure assessments compared with pollution, water abstraction or land-use change. Managers facing the Directive’s requirement to produce cost-effective Programmes of Measures are left guessing where to act, often relying on unstructured expert judgement and reacting site by site rather than planning at the scale of the whole basin. Worse, uncoordinated local restrictions can simply push crowds from a regulated site to an unregulated one downstream, displacing the problem rather than solving it.

The scientific literature has not helped. Angling and navigation have attracted thousands of publications per year, while bathing and canyoning, despite booming in popularity and often being intensely concentrated in space, generate fewer than ten studies annually. This imbalance matters because the impacts differ sharply by activity. Canyoning, with its repeated walking, climbing and sliding along stream channels, tramples riverbeds, mobilises sediment and damages riparian vegetation, reducing the abundance and diversity of benthic macroinvertebrates. Bathing raises turbidity and nutrient concentrations and introduces sunscreen chemicals, although measured concentrations often fall below toxicity thresholds; bathers can also shift the composition of benthic bacterial communities, with unknown consequences for ecosystem functioning. Motorised navigation adds fuel and hydrocarbon contamination, sediment resuspension and noise, while boats and fishing gear alike can spread invasive species. In Mediterranean rivers, where summer crowds coincide with the lowest flows of the year, these disturbances hit ecosystems at their most vulnerable moment.

To build a workable assessment, the team combined hard data with structured human knowledge. They compiled spatial layers for all four activities from official cartography, navigation declarations, environmental informant programmes, federation databases and even georeferenced swimming spots scraped from Google Maps and Wikiloc. Thirty-four semi-structured interviews with stakeholders drawn from an initial pool of 1,558 actors, including administrators, user organisations, companies and researchers, supplied context on where activities peak, what impacts people observe and which measures are realistic. Crucially, the interviews never replaced quantitative data; they complemented it, flagging data gaps and grounding the scoring of management options in practical experience rather than theory.

The quantitative core of the method is elegantly simple in concept: pressure equals the intensity of recreational use relative to the capacity of the receiving water body. Angling pressure, for example, was calculated from daily licence equivalents weighted by fishing modality, with salmonid harvest zones weighted twenty times more than catch-and-release zones, then normalised by river length and mean annual discharge estimated with a calibrated SWAT+ hydrological model. Navigation pressure weighted internal combustion engines twenty times more than rowing or sailing. Each water body was then classified as having null, low, moderate or high pressure using the Jenks natural breaks algorithm, with a separate ‘no data’ category preserving uncertainty rather than pretending absent evidence means absent pressure.

The results confirmed strong spatial clustering. Angling was the most widespread activity, yet only 5 percent of water bodies reached high pressure, concentrated in salmonid harvest reaches and intensively fished reservoirs. Navigation was overwhelmingly benign: 90 percent of water bodies showed null pressure, with the few high-pressure cases tied to reservoirs permitting motorised boats. The real story lay in the data gaps. Bathing was identified in 97 water bodies, but visitor counts existed for only 14 of them, leaving 86 percent unquantifiable. Canyoning fared similarly, with 74 percent of affected water bodies lacking descent data. In other words, the activities growing fastest and least studied are precisely those managers cannot currently measure, a systematic blind spot that likely leads to underestimating total recreational pressure.

From the assessment, the researchers compiled 26 candidate management measures, each summarised in a standardised factsheet covering cost, complexity, implementation time, social acceptance and expected effectiveness. Two composite indices, one for effectiveness and one for difficulty, then ranked the options. The winners combined broad reach with low barriers: extending the criteria for prohibiting bathing, awareness campaigns on bathing impacts, banning internal combustion engines across all reservoirs, and prohibiting fishing in trout genetic reserves all scored highly. At the bottom sat expensive infrastructure projects such as artificial channels for water skiing and adaptation of public swimming pools, whose difficulty was driven mainly by economic cost. Notably, difficulty was shaped more by cost and social acceptance than by technical complexity or time, a finding with clear implications for what agencies can realistically deliver.

The final piece is a rule-based decision-support algorithm that walks each water body through a logical sequence. Low or null pressure means maintaining current regulation. Moderate or high pressure triggers impact monitoring, scaled up for specially protected sites. If significant ecological impacts are confirmed, specially protected water bodies move toward eliminating the pressure entirely, while unprotected ones receive pressure-reduction measures; where impacts are not significant, precautionary reduction applies in protected areas and continued monitoring elsewhere. The algorithm was reviewed by basin technicians and reproduced the decision logic managers already use informally, but now in a transparent, reproducible form. When unquantified bathing or canyoning activity was conservatively treated as high pressure, the framework correctly flagged that data collection, not regulation, should come first.

Prioritisation across the basin distilled the message further: roughly 10 percent of water bodies, those combining aggregated pressure of four or higher with at least one conservation designation such as protected natural areas, fluvial natural reserves or trout genetic reserves, emerge as the prime targets for intervention. The authors are candid about limitations. Annual-average indicators miss the seasonal intensity of summer low-flow peaks, the stakeholder sample is purposive rather than statistically representative, and bathers’ informal perspectives were harder to capture than those of organised angling clubs. The algorithm has been validated qualitatively, not against historical management outcomes, because no such systematic records exist. Yet the framework’s modular design, built from data types most regions already possess or can generate cheaply, makes it transferable to any water-scarce, tourism-intensive basin where recreational pressure is outpacing management capacity. Its deepest insight may be the simplest: in data-poor conservation, knowing what you do not know is itself a management action, and spending a little on counting swimmers and canyoners may buy more ecological protection than any single restrictive rule.

Subject of Research: Prioritising recreational pressures on freshwater ecosystems for management action under uncertainty

Article Title: From pressure indicators to management action: prioritising recreational pressures in freshwater ecosystems under uncertainty

Article References: Pueyo-Ros, J., Acuña, V., & Freixa, A. (2026). From pressure indicators to management action: prioritising recreational pressures in freshwater ecosystems under uncertainty. Environmental and Sustainability Indicators, 32, Article 101535. https://doi.org/10.1016/j.indic.2026.101535

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101535

Keywords: freshwater ecosystems, recreational pressures, Water Framework Directive, bathing, angling, canyoning, navigation, decision-support algorithm, Mediterranean rivers, pressure indicators, stakeholder interviews, environmental management

The relationship between the urban environment and public health is one of the most robustly established findings in modern epidemiology. The quality of housing, the design of transport infrastructure, the availability of green space and the walkability of neighbourhoods all measurably influence the risk that residents will develop life-threatening conditions. Poorly connected communities with limited access to parks and active travel options show elevated rates of obesity, cardiovascular disease, respiratory illness and several cancers. Yet despite decades of evidence, improving urban environments as a preventative public health measure remains extraordinarily complex, because it demands coordinated action from multiple actors with different mandates, budgets and priorities. Planning authorities, housing developers, transport agencies and health services each hold only part of the levers required to create healthier places, and no single organisation bears the full cost of the diseases that bad design can produce.

It is precisely this fragmentation that the researchers set out to address. To assess how economic evidence could support more integrated decision-making, the team conducted 167 qualitative interviews with key stakeholders drawn from across England’s urban development system, spanning national and local government, private industry and civil society. The interviews explored in depth how the HAUS tool could support collaboration and informed decision-making across sectors that rarely share a common evidence base or a common metric of success. What emerged was a striking consensus: stakeholders recognised the value of HAUS as a new way to support shared decision-making and to create incentives for organisations to work together toward better health outcomes, precisely because it assigns an economic value to impacts that have historically been invisible in development appraisals.

The technical core of HAUS is a valuation model that links specific features of the environment to health outcomes and their associated economic costs. The tool quantifies and monetises changes in disease occurrence and premature mortality linked with different urban development interventions and affecting local populations. In practical terms, a proposal to add walkable streets, expand green infrastructure or improve housing quality can be assessed not only in terms of construction costs and property values, but also in terms of the expected reduction in NHS treatment costs, productivity losses and the broader societal burden of illness. By translating health outcomes into economic terms, the tool helps decision-makers grasp the long-term value of healthier urban environments and supports more informed investment and planning decisions that might otherwise be dismissed on short-term financial grounds.

The tool did not appear from nowhere. It was initially developed during an earlier research pilot and was further refined throughout the project in collaboration with the UK’s Ministry of Housing, Communities and Local Government, giving it an unusually direct route from academic prototype to policy application. That collaboration has now borne institutional fruit: the ministry has adopted HAUS in its appraisal guides for local authorities, embedding health valuation into the standard machinery of English planning assessment. For a field in which public health arguments have long struggled to compete with housing delivery targets and economic growth imperatives, this represents a significant shift in what evidence counts when the future of a city is decided.

Dr Andrew Barnfield, Senior Lecturer in public health at the University of East London and co-author of the study, emphasised that the tool changes what decision-makers are able to see. ‘The HAUS tool enables decision makers to account for health costs that are linked with the urban environment,’ he said. ‘As our work shows, this is vital for making healthier and more equitable places.’ The equity dimension matters because the health burden of poor urban design falls disproportionately on disadvantaged communities, which are more likely to live near major roads, in lower-quality housing and with limited access to green space. By making these costs explicit, HAUS gives advocates for those communities a quantitative argument that resonates in boardrooms and town halls alike.

Professor Sarah Ayres, from the University of Bristol’s School for Policy Studies, framed the development as a genuine methodological milestone. ‘The collaboration between TRUUD and the Ministry of Housing, Communities and Local Government has created a version of the Health Appraisal of Urban Systems model which is to be used for housing, community and local government interventions,’ she said. ‘For the first time, there are now methods to quantify and value the potential health impacts of urban interventions for specific populations.’ The reference to TRUUD, the research consortium on urban health decarbonisation and decision-making of which the three universities are part, underlines the scale of the effort required to move such tools from theory into the working routines of government.

Dr Geoff Bates, from the University of Bath’s Institute for Policy Research, argued that the economic framing is not a concession to fiscal orthodoxy but a strategic necessity. ‘Making the economic case to pursue preventative policies is one way that can persuade policymakers to act to improve long-term health and wellbeing,’ he said. ‘Improving policymaker access to evidence and tools like HAUS that demonstrate the savings to the public purse from investing in healthier housing and urban environments is a step towards improving public health.’ The logic is familiar from other domains of preventative policy: the costs of disease are diffuse and delayed, while the costs of intervention are immediate and concentrated, and only tools that render future savings visible can rebalance that asymmetry in political decision-making.

The findings arrive at a moment when the pressures on urban systems are intensifying. Rising obesity rates, an ageing population, persistent air pollution and the health impacts of climate change all converge on the built environment, and health services across the developed world are increasingly looking upstream toward prevention. The researchers conclude that HAUS provides valuable evidence to encourage cross-sector collaboration and to embed preventative public health into urban development decisions, shifting the question from whether cities can afford to prioritise health to whether they can afford not to. If the tool’s adoption by national government spreads through local authority practice, the healthier city may cease to be an aspiration and become, at last, an audited line in the appraisal.

Subject of Research: Economic valuation of public health impacts in urban development decision-making

Article Title: Economic tool could help cities prioritize public health in urban development

Article References: Economic tool could help cities prioritize public health in urban development. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: urban development, public health, HAUS tool, economic valuation, planning policy, prevention, health equity, built environment, stakeholder interviews, England, University of East London, ministry adoption