Policy impact pathways of climate-related urban health vulnerability - A retrospective analysis.

Climate change-related health risks are likely to become more prevalent in cities. Cities are also key actors in adaptation to these risks. Adaptation can take place through intentional measures to reduce vulnerability or exposure and unintentionally through other urban policy processes and outcomes. However, complex and dynamic relations between urban policy impacts and vulnerability development are an understudied phenomena. This limits the understanding of how urban climate-related health risks emerge and evolve. We examine urban policy pathways that influence vulnerability to climate-related health impacts with a most similar - most different case study. With a qualitative retrospective analysis of four urban areas in Finland we unveil the mechanism of how urban policy affects urban environment over time and how these impacts and changes shape vulnerability. Contrasting the most different cases, we show that urban policy impacts set differing preconditions to adaptation between local districts. We conclude by suggesting that to adapt to future challenges in cities with respect to social and ecological justice, it is necessary to mainstream adaptation into urban policies with continuous cross-sector and multi-level dialogue about the development of vulnerability.

Detecting Spatial Patterns of Peatland Greenhouse Gas Sinks and Sources with Geospatial Environmental and Remote Sensing Data.

Peatlands play a key role in the circulation of the main greenhouse gases (GHG) - methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O). Therefore, detecting the spatial pattern of GHG sinks and sources in peatlands is pivotal for guiding effective climate change mitigation in the land use sector. While geospatial environmental data, which provide detailed spatial information on ecosystems and land use, offer valuable insights into GHG sinks and sources, the potential of directly using remote sensing data from satellites remains largely unexplored. We predicted the spatial distribution of three major GHGs (CH4, CO2, and N2O) sinks and sources across Finland. Utilizing 143 field measurements, we compared the predictive capacity of three different data sets with MaxEnt machine-learning modeling: (1) geospatial environmental data including climate, topography and habitat variables, (2) remote sensing data (Sentinel-1 and Sentinel-2), and (3) a combination of both. The combined dataset yielded the highest accuracy with an average test area under the receiver operating characteristic curve (AUC) of 0.845 and AUC stability of 0.928. A slightly lower accuracy was achieved using only geospatial environmental data (test AUC 0.810, stability AUC 0.924). In contrast, using only remote sensing data resulted in reduced predictive accuracy (test AUC 0.763, stability AUC 0.927). Our results suggest that (1) reliable estimates of GHG sinks and sources cannot be produced with remote sensing data only and (2) integrating multiple data sources is recommended to achieve accurate and realistic predictions of GHG spatial patterns.

Mainstreaming nature-based solutions through five forms of scaling: Case of the Kiiminkijoki River basin, Finland.

Nature-based solutions (NBS) are considered as means to tackle climate change and biodiversity loss while simultaneously enhancing human well-being. Yet, it is still poorly understood how NBS could be mainstreamed. We address this gap by proposing a framework on NBS and employing it in Finland's Kiiminkijoki River basin through participatory workshops and a questionnaire. We examine socio-environmental challenges and visions, existing and emerging NBS to reach the visions, and ways to scale-up NBS to a river basin level. In the river basin, water quality is the priority challenge, due to its relationships with local culture, climate change, and biodiversity. Our results consider how (1) to ensure the relevance of NBS for local actors, (2) instrumental, intrinsic, and relational value perspectives can be enhanced simultaneously by NBS, and (3) site specific NBS can be mainstreamed (i.e., by scaling up, down, out, in, deep) to the river basin level and beyond.

After-use of peat extraction sites - A systematic review of biodiversity, climate, hydrological and social impacts.

After drainage for forestry and agriculture, peat extraction is one of the most important causes of peatland degradation. When peat extraction is ceased, multiple after-use options exist, including abandonment, restoration, and replacement (e.g., forestry and agricultural use). However, there is a lack of a global synthesis of after-use research. Through a systematic review of 356 peer-reviewed scientific articles, we address this research gap and examine (1) what after-use options have been studied, (2) what the studied and recognized impacts of the after-use options are, and (3) what one can learn in terms of best practices and research gaps. The research has concentrated on the impacts of restoration (N = 162), abandonment (N = 72), and replacement (N = 94), the latter of which consists of afforestation (N = 46), cultivation (N = 34) and creation of water bodies (N = 14). The studies on abandonment, restoration, and creation of water bodies have focused mostly on analyzing vegetation and greenhouse gas (GHG) fluxes, while the studies assessing afforestation and cultivation sites mostly evaluate the provisioning ecosystem services. The studies show that active restoration measures speed-up vegetation recolonization on bare peat areas, reduce GHG emissions and decrease negative impacts on water systems. The most notable research gap is the lack of studies comparing the environmental and social impacts of the after-use options. Additionally, there is a lack of studies focusing on social impacts and downstream hydrology, as well as long-term monitoring of GHG fluxes. Based on the reviewed studies, a comparison of the impacts of the after-use options is not straightforward. We emphasize a need for comparative empirical research in the extracted sites with a broad socio-ecological and geographical context.

Factors influencing vulnerability to climate change-related health impacts in cities - A conceptual framework.

Climate change will have adverse impacts on human health, which are amplified in cities. For these impacts, there are direct, indirect, and deferred pathways. The first category is well-studied, while indirect and deferred impacts are not well-understood. Moreover, the factors moderating the impacts have received little attention, although understanding these factors is critical for adaptation. We developed a conceptual framework that shows the pathways of climate impacts on human health, focusing specifically on the factors of urban environment moderating the emergence and severity of these health impacts. Based on the framework and literature review, we illustrate the mechanisms of direct, indirect, and deferred health impact occurrence and the factors that exacerbate or alleviate the severity of these impacts, thus presenting valuable insights for anticipatory adaptation. We conclude that an integrated systemic approach to preventing health risks from climate change can provide co-benefits for adaptation and address multiple health risks. Such an approach should be mainstreamed horizontally to all sectors of urban planning and should account for the spatiotemporal aspects of policy and planning decisions and city complexity.

Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic.

Across the Arctic, the net ecosystem carbon (C) balance of tundra ecosystems is highly uncertain due to substantial temporal variability of C fluxes and to landscape heterogeneity. We modeled both carbon dioxide (CO2 ) and methane (CH4 ) fluxes for the dominant land cover types in a ~100-km2 sub-Arctic tundra region in northeast European Russia for the period of 2006-2015 using process-based biogeochemical models. Modeled net annual CO2 fluxes ranged from -300 g C m-2  year-1 [net uptake] in a willow fen to 3 g C m-2  year-1 [net source] in dry lichen tundra. Modeled annual CH4 emissions ranged from -0.2 to 22.3 g C m-2  year-1 at a peat plateau site and a willow fen site, respectively. Interannual variability over the decade was relatively small (20%-25%) in comparison with variability among the land cover types (150%). Using high-resolution land cover classification, the region was a net sink of atmospheric CO2 across most land cover types but a net source of CH4 to the atmosphere due to high emissions from permafrost-free fens. Using a lower resolution for land cover classification resulted in a 20%-65% underestimation of regional CH4 flux relative to high-resolution classification and smaller (10%) overestimation of regional CO2 uptake due to the underestimation of wetland area by 60%. The relative fraction of uplands versus wetlands was key to determining the net regional C balance at this and other Arctic tundra sites because wetlands were hot spots for C cycling in Arctic tundra ecosystems.