# **6. Conclusions**

This paper provides a novel analysis based on the combination of high‐resolution, geo‐spatial data and household data from Vietnam. Despite several limitations related to the available data sets, this study reveals the first empirical insights into the potential role of environmental risks in the livelihoods of poor people, using data sets that have become recently available and measuring a comprehensive set of environmental variables.

The findings show the following: (i) at district level there are large hotspots of high poverty and environmental risks; (ii) ethnic minorities and poor households are much more exposed to multiple environmental risks than other groups, and also within rural and urban zones poorer households live in communes exposed to higher environmental risks; and (iii) environmental risks relate to lower consumption levels, but less so to consumption changes over time. In particular, households in communes with steeper slopes and higher rainfall and temperature variability and greater flood and drought hazards have lower consumption levels, while those living in communes with higher air pollution have lower consumption growth. Although causal relationship between risks and consumption cannot be clearly established with the data, these findings suggest that poor people are disproportionally exposed to environmental risks.

More work is needed to confirm that environmental risks pose a threat to poverty eradication and shared prosperity. First, longer time‐series data is needed to evaluate whether environmental conditions have long‐ lasting impacts on household living standards. Second, this study mostly relies on global data sets from remote sensing or modeling work, which needs to be verified and refined with monitored data at the subnational level – optimally from ground stations. Moreover, this study could only define historic risk profiles and not the actual environmental conditions and risk materialization within the survey years. The expansion of these analyses with such data will be an important area for deepening the findings of this work.

Even in the absence of such analyses, some evidence already exists that shows the detrimental impacts of environmental risks on poverty and household welfare. An accompanying study, for example, shows that actual variation in rainfall and temperature conditions is related to significant consumption and income effects also for poor people (Narloch, 2016). In addition, other work has shown the negative welfare and poverty impacts of flood and drought events (Arouri et al., 2015; Bui et al., 2014; Thomas et al., 2010). Moreover, poor people could be affected by environmental risks in many ways that go beyond income and consumption effects, such as detrimental health impacts or a decline in the quality of life due to poor environmental conditions. Such impacts cannot be measured with the existing household data.

In light of growing pressures due to population growth, economic development and climate change, environmental risks need to be considered in poverty reduction policies. Green growth actions that allow economic development without excessively harmful environmental impacts, for example through increased resource efficiency, will help to reduce the environmental burden on poor people. Moreover, ecosystem‐based adaptation could strengthen ecosystem resilience and reduce environmental risks, while improving the livelihoods of people depending on these ecosystems. Carefully designed land‐use planning policies that encourage resettlements and avoid new settlements in high risk areas are another key strategy to reduce exposure to environmental risks, but should be paired with investments in livelihood support and improved mobility.

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