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It cannot be denied that reflexivity has become a must in social science methodological discourse in recent decades. The uses and functions of reflexivity in the research process have been well addressed historically, be it with regard to researchers' subjectivity, their perspectivity shaped by social origin and biographical life path, or their possible asymmetrical power relations with investigated actors. Nevertheless, we see an urgent need to dis-cuss these issues. We claim that the practice of reflexivity, seriously shaken by the current transformation of (the understandings of) academic knowledge production, has become a challenging duty to fulfill. There is no straight and easy answer to the big questions of "for whom" and "for what purpose" do we produce "what kind of" knowledge and "how." Struggling for an appropriate positioning within global societal developments, we dedicate this special issue to the search for a critical, and the exploration of a lucid, (self-)reflection of academic research. In this respect, this special issue, Positionality Reloaded: Debating the Dimensions of Reflexivity in the Relationship Between Science and Society, sets out to explore how coexisting yet diverse conceptions of academic research and knowledge production can be reflexively considered and related to each other from an epistemological, ethico-normative, and ontological point of view.

Low-cost air quality sensors offer significant potential for enhancing urban air quality networks by providing higher-spatiotemporal-resolution data needed, for example, for evaluation of air quality interventions. However, these sensors present methodological and deployment challenges which have historically limited operational ability. These include variability in performance characteristics and sensitivity to environmental conditions. In this work, we investigate field "baselining" and interference correction using random forest regression methods for low-cost sensing of NO 2 , PM 10 (particulate matter) and PM 2.5 . Model performance is explored using data obtained over a 7-month period by real-world field sensor deployment alongside reference method instrumentation. Workflows and processes developed are shown to be effective in normalising variable sensor baseline offsets and reducing uncertainty in sensor response arising from environmental interferences. We demonstrate improvements of between 37 % and 94 % in the mean absolute error term of fully corrected sensor datasets; this is equivalent to performance within ±2.6 ppb of the reference method for NO 2 , ±4.4 µ g m −3 for PM 10 and ±2.7 µ g m −3 for PM 2.5 . Expanded-uncertainty estimates for PM 10 and PM 2.5 correction models are shown to meet performance criteria recommended by European air quality legislation, whilst that of the NO 2 correction model was found to be narrowly ( ∼5 %) outside of its acceptance envelope. Expanded-uncertainty estimates for corrected sensor datasets not used in model training were 29 %, 21 % and 27 % for NO 2 , PM 10 and PM 2.5 respectively.

Low-cost air quality sensors offer significant potential for enhancing urban air quality networks by providing higher-spatiotemporal-resolution data needed, for example, for evaluation of air quality interventions. However, these sensors present methodological and deployment challenges which have historically limited operational ability. These include variability in performance characteristics and sensitivity to environmental conditions. In this work, we investigate field "baselining" and interference correction using random forest regression methods for low-cost sensing of NO2, PM10 (particulate matter) and PM2.5. Model performance is explored using data obtained over a 7-month period by real-world field sensor deployment alongside reference method instrumentation. Workflows and processes developed are shown to be effective in normalising variable sensor baseline offsets and reducing uncertainty in sensor response arising from environmental interferences. We demonstrate improvements of between 37 % and 94 % in the mean absolute error term of fully corrected sensor datasets; this is equivalent to performance within ±2.6 ppb of the reference method for NO2, ±4.4 µg m−3 for PM10 and ±2.7 µg m−3 for PM2.5. Expanded-uncertainty estimates for PM10 and PM2.5 correction models are shown to meet performance criteria recommended by European air quality legislation, whilst that of the NO2 correction model was found to be narrowly (∼5 %) outside of its acceptance envelope. Expanded-uncertainty estimates for corrected sensor datasets not used in model training were 29 %, 21 % and 27 % for NO2, PM10 and PM2.5 respectively.

AbstractThe snowline exhibits significant seasonal shifts upward and downward, reflecting the ever-changing dynamics of the seasons and being influenced by climate variations, which can vary annually. These fluctuations profoundly impact the cryosphere, biota, and ecosystem processes in high mountain regions. Despite the critical role of snowline variations, comprehensive information on how actual climate variability affects snow cover trends in the central mountain range of the western Himalayas is scarce. In the 'Pindari' region of the Uttarakhand district, India, which is part of the Himalayas, these challenges are exacerbated by the unchecked growth of anthropogenic activities and the broader impacts of climate change. This study analyses snowline variations in the Pindari glacial region from 1972 to 2018. The findings revealed that the snowline elevation significantly shifted upward between 1972 and 2018. Notably, this research revealed a decrease in snow-covered areas of approximately 5.01 km2 over the course of 46 years. This decrease is attributed to a direct response to the increasing number of high-temperature events that occurred during this extended period. This study emphasizes the urgent need for conservation measures in the study region and similar high mountains to combat global warming and safeguard the snowline, which serves as a visible proxy indicator to safeguard high-altitude Himalayan glaciers.

We acknowledge seed grants from the Leverhulme Trust, Royal Society and UKIERI. Natural Environment Research Council Argon Isotope Facility grant IP-1267-1111 funded the argon analyses. A.S. was supported by a IIT-K PhD fellowship. J-P.B. receives funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme ERC-2014-StG 639904 – RELOS. ; Urbanism in the Bronze-age Indus Civilisation (~4.6–3.9 thousand years before the present, ka) has been linked to water resources provided by large Himalayan river systems, although the largest concentrations of urban-scale Indus settlements are located far from extant Himalayan rivers. Here we analyse the sedimentary architecture, chronology and provenance of a major palaeochannel associated with many of these settlements. We show that the palaeochannel is a former course of the Sutlej River, the third largest of the present-day Himalayan rivers. Using optically stimulated luminescence dating of sand grains, we demonstrate that flow of the Sutlej in this course terminated considerably earlier than Indus occupation, with diversion to its present course complete shortly after ~8 ka. Indus urban settlements thus developed along an abandoned river valley rather than an active Himalayan river. Confinement of the Sutlej to its present incised course after ~8 ka likely reduced its propensity to re-route frequently thus enabling long-term stability for Indus settlements sited along the relict palaeochannel. ; Publisher PDF ; Peer reviewed

Frontmatter --Inhalt --Am Ende der Globalisierung --Von der Globalisierung zur Refiguration --Raumfiguren, Raumkulturen und die Refiguration von Räumen --VERHEIMATEN --Verräumlichungen von Politiken --Dynamiken und Praktiken räumlicher Restrukturierung --Infrastrukturierung von Wissensräumen --Grenzen erkunden --Die Refiguration digitalisierter Räume --Kontrollzentralen und die Polykontexturalisierung von Räumen --Digitale Planung, digitalisiertes Planungshandeln und mediatisierte Konstruktionen von Räumen --Die Refiguration von Räumen durch smarte Apartmentkomplexe --Die visuelle Refiguration urbaner Zukünfte --Das CAMPP-Modell des Zusammenhangs von Bedeutung und Zugänglichkeit öffentlicher Orte und seine Anwendung auf lokative Medien --Global-lokales Raumwissen --Global Middle Class? --Imaginationen der Globalisierung --Die karibische Banane im deutschen Supermarkt --Nebenbei und Nebenan --Global-lokaler Alltag unter Bedingungen von Refiguration --Rückblick und Ausblick --Interdisziplinarität als polykontexturale Wissensproduktion --Empirische Wissenschaftstheorie --AutorInneninformationen