Carbon, Footprints, and Trade: New Study Maps How Climate Pressures Reshape Tourism Across Asia-Pacific

Tourism is one of the world’s most visible barometers of environmental change, and a new study suggests the relationship between climate pressures and international travel is far more complicated than average-based statistics have led policymakers to believe. Research published in Theoretical and Applied Climatology examines how carbon dioxide emissions, ecological footprint, trade openness, and economic growth shape international tourism arrivals across ten Asia-Pacific economies between 2001 and 2024. The findings reveal a striking pattern of heterogeneity: the very factors that appear to boost tourism in some contexts can undermine it in others, depending on where a destination sits in the global distribution of visitor volumes.

The study, authored by Chenchen Wu of Anhui Normal University in China, departs from conventional econometric practice in a way that matters for how governments interpret the numbers. Most analyses of the climate-tourism nexus rely on mean-based regression techniques, which estimate a single average effect and implicitly assume the relationship holds everywhere. Wu instead applies the Method of Moments Quantile Regression approach, a technique introduced by Machado and Silva in 2019 that estimates effects across the entire conditional distribution of the outcome variable. In practical terms, this means the analysis can distinguish between what drives tourism in destinations receiving relatively few arrivals and what drives tourism in destinations already flooded with visitors, rather than collapsing both into one misleading average.

The dataset draws on World Bank records for ten Asia-Pacific economies over nearly a quarter century, a period that encompasses the region’s extraordinary tourism boom, the global financial crisis, and the catastrophic collapse and recovery of international travel surrounding the COVID-19 pandemic. Four explanatory variables anchor the analysis. Carbon emissions capture the carbon-intensive character of economic activity. Ecological footprint, a measure developed by Wackernagel and Rees, quantifies the total biologically productive area an economy consumes, making it a broader indicator of environmental degradation than emissions alone. Trade openness reflects a country’s integration into global commerce, and gross domestic product stands in for overall economic scale.

The results on carbon emissions are perhaps the most counterintuitive. Across the lower, median, and upper-median quantiles of the arrivals distribution, carbon emissions show a positive and statistically significant association with tourism arrivals. This may seem paradoxical at first, but it is consistent with the idea that in developing and middle-income destinations, carbon-intensive industrial activity and tourism growth often rise together as part of the same expansionary economic process: more flights, more hotels, more energy consumption, and more visitors arriving in lockstep. Yet at the very highest quantile of arrivals, among the region’s most heavily visited destinations, the carbon effect loses statistical significance entirely. Carbon-intensive activity, the study suggests, matters most for destinations seeing low to medium volumes of arrivals, while at the top of the distribution other forces dominate.

The ecological footprint tells a much darker and more uniform story. Unlike carbon emissions, the ecological footprint is negative and statistically significant across every quantile examined. This means that general environmental degradation systematically suppresses international visitation regardless of whether a destination currently receives few tourists or millions of them. The implication is sobering for tourism-dependent economies: while the carbon-tourism link may weaken as destinations mature, the broader erosion of the natural capital that attracts visitors in the first place, clean beaches, healthy reefs, intact forests, breathable air, exacts a penalty everywhere. Environmental degradation, in other words, is not a problem that afflicts only struggling destinations; it is a structural threat that follows an economy up the entire arrivals ladder.

Trade openness emerges as the single most powerful positive driver in the analysis. Its effect is statistically significant across the distribution and peaks at the median quantile, confirming the role of commercial connectivity as a critical engine of cross-border tourism mobility. This finding aligns with a long tradition in the tourism economics literature, including gravity-model studies showing that transport infrastructure and economic linkages facilitate international visitor flows. The mechanism is intuitive: economies deeply embedded in global trade networks accumulate the airports, airlines, business travel, familiarity, and visa-friendly relationships that make leisure travel easier. Business trips seed future holidays, and trade agreements quietly double as tourism agreements.

GDP, by contrast, shows a positive association with arrivals throughout the distribution, but the marginal effect shrinks at higher quantiles. Economic growth fuels tourism most powerfully in destinations that are still building their visitor base; among the region’s tourism giants, additional GDP buys progressively fewer incremental arrivals. This pattern echoes the tourism-induced environmental Kuznets curve hypothesis explored in prior literature, in which the environmental and economic dynamics of tourism shift character as destinations move through different stages of development. It also carries a warning for mature destinations: growth alone will not sustain arrivals if the environmental foundations of attractiveness are allowed to decay.

Methodologically, the study is careful about the pitfalls that plague panel data in environmental economics. The analysis builds on a battery of diagnostic tests drawn from the modern econometrics literature, including panel unit root tests that account for cross-sectional dependence, slope homogeneity tests in the tradition of Pesaran and Yamagata, and cointegration testing to establish long-run relationships among the variables. The Method of Moments Quantile Regression framework then allows slope coefficients to vary across quantiles while handling the heterogeneity that ordinary least squares would average away. The author reports that the distributional differences are substantial enough that a single mean-based estimate would obscure, and in places invert, the true picture.

The policy implications are where the study becomes genuinely provocative. Because the climate-tourism relationship varies systematically across the arrivals distribution, Wu argues that environmental and tourism policy should be differentially designed according to a country’s relative position in the global tourism hierarchy. Emerging destinations with low to moderate arrivals, where carbon emissions and tourism still move together, face a window of opportunity to decouple the two before carbon-intensive lock-in takes hold. Mature, high-volume destinations, where the carbon effect fades but ecological footprint damage persists, should prioritize environmental restoration and carrying-capacity management over sheer growth. And for economies in the middle of the distribution, where trade openness exerts its strongest pull, the evidence suggests that commercial integration and environmental protection are complements rather than rivals: the connectivity that draws visitors is only worth as much as the environment they come to see.

The broader stakes are hard to overstate. Tourism contributes substantially to global carbon emissions, with recent research in Nature Communications estimating the drivers of tourism’s climate footprint, and the sector is simultaneously among the most vulnerable to climate impacts, from coral bleaching to heat extremes. The new findings add a distributional dimension to this feedback loop: environmental degradation does not merely threaten tourism in the abstract, it threatens it unevenly, punishing destinations at every level of development while the carbon-tourism coupling that fuels the problem is strongest precisely where destinations can least afford to manage it. For the ten Asia-Pacific economies studied, and for tourism-dependent nations everywhere, the message is that averages lie. The future of tourism will be written not in a single regression coefficient but across an entire distribution, and the destinations that read their own position carefully may be the ones that keep their beaches, forests, and visitors intact.

Subject of Research: Distributional analysis of how carbon emissions, ecological footprint, trade openness, and GDP affect international tourism arrivals in Asia-Pacific economies from 2001 to 2024

Article Title: Carbon, carrying capacity, and connectivity: Distributional evidence on the climate change-tourism nexus in Asia–Pacific economies

Article References: Wu, C. (2026). Carbon, carrying capacity, and connectivity: Distributional evidence on the climate change-tourism nexus in Asia–Pacific economies. Theoretical and Applied Climatology, 157(10), Article 681. https://doi.org/10.1007/s00704-026-06612-1

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06612-1

Keywords: climate change, tourism economics, carbon emissions, ecological footprint, quantile regression, trade openness, Asia-Pacific, international tourism arrivals, environmental degradation, GDP, sustainable tourism, econometrics