Kajian Tipologi dalam Pembentukan Karakter Visual dan Struktur Kawasan (Studi Kasus: Kawasan Ijen, Malang)

Tulisan ini bertujuan untuk mengidentifikas karakteristik dari periodisasi arsitektur berdasarkan wujud fisik dan tampilan visual dalam skala mezo (ruang kota) di Kawasan Ijen. Kawasan ini merupakan bagian dari Kota Malang yang tidak terlepas dari sosok Karstens sebagai seorang arsitek dan perencana kota yang mengembangkan konsep Planned Development City pada beberapa kota di Indonesia yang memiliki fungsi dan peranan dalam struktur pemerintahan Kolonial Belanda. Metode yang digunakan dalam kajian ini adalah deskriptif-kualitatif, dengan komponen pembentuk tampilan visual kawasan sebagai unit analisis. Tampilan visual kawasan dianalisis dalam lingkup kawasan (urban space) dengan pendekatan tipologi terhadap bangunan dan ruang kota yang dirancang oleh Karstens pada Kawasan Ijen. Fasad bangunan sebagai salah satu komponen pembentuk tampilan visual dibahas sebagai suatu kesatuan massa dan bentuk bangunan yang membentuk urban corridor wall pada kawasan ije

Information visualization for mobile devices: A novel approach based on the MagicEyeView

Visualization on mobile devices not only means accommodating to a small screen space, but also widely different aspect ratios. Improving on the MagicEyeView algorithm, this paper presents a visualization technique that is better suited to screens with skewed aspects ratios. The presented approach is a focus+context visualization effort which employs distortion of coordinate scales and a "fisheye" technique. The visualization algorithm is evaluated in the problem domain of business management and the presentation of "Key Performance Indicators"

Atmospheric transport and chemistry of trace gases in LMDz5B: evaluation and implications for inverse modelling

Representation of atmospheric transport is a major source of error in the estimation of greenhouse gas sources and sinks by inverse modelling. Here we assess the impact on trace gas mole fractions of the new physical parameterizations recently implemented in the atmospheric global climate model LMDz to improve vertical diffusion, mesoscale mixing by thermal plumes in the planetary boundary layer (PBL), and deep convection in the troposphere. At the same time, the horizontal and vertical resolution of the model used in the inverse system has been increased. The aim of this paper is to evaluate the impact of these developments on the representation of trace gas transport and chemistry, and to anticipate the implications for inversions of greenhouse gas emissions using such an updated model. Comparison of a one-dimensional version of LMDz with large eddy simulations shows that the thermal scheme simulates shallow convective tracer transport in the PBL over land very efficiently, and much better than previous versions of the model. This result is confirmed in three-dimensional simulations, by a much improved reproduction of the radon-222 diurnal cycle. However, the enhanced dynamics of tracer concentrations induces a stronger sensitivity of the new LMDz configuration to external meteorological forcings. At larger scales, the inter-hemispheric exchange is slightly slower when using the new version of the model, bringing them closer to observations. The increase in the vertical resolution (from 19 to 39 layers) significantly improves the representation of stratosphere/troposphere exchange. Furthermore, changes in atmospheric thermodynamic variables, such as temperature, due to changes in the PBL mixing modify chemical reaction rates, which perturb chemical equilibriums of reactive trace gases. One implication of LMDz model developments for future inversions of greenhouse gas emissions is the ability of the updated system to assimilate a larger amount of high-frequency data sampled at high-variability stations. Others implications are discussed at the end of the paper

Canopy uptake dominates nighttime carbonyl sulfide fluxes in a boreal forest

Nighttime vegetative uptake of carbonyl sulfide (COS) can exist due to the incomplete closure of stomata and the light independence of the enzyme carbonic anhydrase, which complicates the use of COS as a tracer for gross primary productivity (GPP). In this study we derived nighttime COS fluxes in a boreal forest (the SMEAR II station in Hyytiälä, Finland; 61°51′ N, 24°17′ E; 181 m a.s.l.) from June to November 2015 using two different methods: eddy-covariance (EC) measurements (FCOS-EC) and the radon-tracer method (FCOS-Rn). The total nighttime COS fluxes averaged over the whole measurement period were −6.8 ± 2.2 and −7.9 ± 3.8 pmol m−2 s−1 for FCOS-Rn and FCOS-EC, respectively, which is 33–38 % of the average daytime fluxes and 21 % of the total daily COS uptake. The correlation of 222Rn (of which the source is the soil) with COS (average R2  =  0.58) was lower than with CO2 (0.70), suggesting that the main sink of COS is not located at the ground. These observations are supported by soil chamber measurements that show that soil contributes to only 34–40 % of the total nighttime COS uptake. We found a decrease in COS uptake with decreasing nighttime stomatal conductance and increasing vapor-pressure deficit and air temperature, driven by stomatal closure in response to a warm and dry period in August. We also discuss the effect that canopy layer mixing can have on the radon-tracer method and the sensitivity of (FCOS-EC) to atmospheric turbulence. Our results suggest that the nighttime uptake of COS is mainly driven by the tree foliage and is significant in a boreal forest, such that it needs to be taken into account when using COS as a tracer for GPP

Inferring Rn-222 soil fluxes from ambient Rn-222 activity and eddy covariance measurements of CO2

We present a new methodology, which we call Single Pair of Observations Technique with Eddy Covariance (SPOT-EC), to estimate regional-scale surface fluxes of 222Rn from tower-based observations of 222Rn activity concentration, CO2 mole fractions and direct CO2 flux measurements from eddy covariance. For specific events, the regional (222Rn) surface flux is calculated from short-term changes in ambient (222Rn) activity concentration scaled by the ratio of the mean CO2 surface flux for the specific event to the change in its observed mole fraction. The resulting 222Rn surface emissions are integrated in time (between the moment of observation and the last prior background levels) and space (i.e. over the footprint of the observations). The measurement uncertainty obtained is about ±15 % for diurnal events and about ±10 % for longer-term (e.g. seasonal or annual) means. The method does not provide continuous observations, but reliable daily averages can be obtained. We applied our method to in situ observations from two sites in the Netherlands: Cabauw station (CBW) and Lutjewad station (LUT). For LUT, which is an intensive agricultural site, we estimated a mean 222Rn surface flux of (0.29 ± 0.02) atoms cm−2 s−1 with values  > 0.5 atoms cm−2 s−1 to the south and south-east. For CBW we estimated a mean 222Rn surface flux of (0.63 ± 0.04) atoms cm−2 s−1. The highest values were observed to the south-west, where the soil type is mainly river clay. For both stations good agreement was found between our results and those from measurements with soil chambers and two recently published 222Rn soil flux maps for Europe. At both sites, large spatial and temporal variability of 222Rn surface fluxes were observed which would be impractical to measure with a soil chamber. SPOT-EC, therefore, offers an important new tool for estimating regional-scale 222Rn surface fluxes. Practical applications furthermore include calibration of process-based 222Rn soil flux models, validation of atmospheric transport models and performing regional-scale inversions, e.g. of greenhouse gases via the SPOT 222Rn-tracer method

Quantifying methane and nitrous oxide emissions from the UK and Ireland using a national-scale monitoring network

The UK is one of several countries around the world that has enacted legislation to reduce its greenhouse gas emissions. In this study, we present top-down emissions of methane (CH4) and nitrous oxide (N2O) for the UK and Ireland over the period August 2012 to August 2014. These emissions were inferred using measurements from a network of four sites around the two countries. We used a hierarchical Bayesian inverse framework to infer fluxes as well as a set of covariance parameters that describe uncertainties in the system. We inferred average UK total emissions of 2.09 (1.65–2.67) Tg yr−1 CH4 and 0.101 (0.068–0.150) Tg yr−1 N2O and found our derived UK estimates to be generally lower than the a priori emissions, which consisted primarily of anthropogenic sources and with a smaller contribution from natural sources. We used sectoral distributions from the UK National Atmospheric Emissions Inventory (NAEI) to determine whether these discrepancies can be attributed to specific source sectors. Because of the distinct distributions of the two dominant CH4 emissions sectors in the UK, agriculture and waste, we found that the inventory may be overestimated in agricultural CH4 emissions. We found that annual mean N2O emissions were consistent with both the prior and the anthropogenic inventory but we derived a significant seasonal cycle in emissions. This seasonality is likely due to seasonality in fertilizer application and in environmental drivers such as temperature and rainfall, which are not reflected in the annual resolution inventory. Through the hierarchical Bayesian inverse framework, we quantified uncertainty covariance parameters and emphasized their importance for high-resolution emissions estimation. We inferred average model errors of approximately 20 and 0.4 ppb and correlation timescales of 1.0 (0.72–1.43) and 2.6 (1.9–20 3.9) days for CH4 and N2O, respectively. These errors are a combination of transport model errors as well as errors due to unresolved emissions processes in the inventory. We found the largest CH4 errors at the Tacolneston station in eastern England, which may be due to sporadic emissions from landfills and offshore gas in the North Sea

Identity politics, core State powers and regional Integration: Europe and beyond

This article concentrates on the path from the development of collective identities to the integration of core state powers. Firstly, we focus on the European experience. We argue that the identities of political, economic, and social elites have been crucial for the evolution of European integration. With regard to mass public opinion, European integration has been made possible by a consensus of EU citizens with inclusive national identities. Most recently, the politicization of EU affairs in many member states has been driven by populist forces mobilizing minorities with exclusive nationalist identities. Secondly, we discuss the extent to which insights from Europe have travelled to other regions of the world. Elites involved in region‐building almost always develop identity narratives linking their national experience to the respective regions. Moreover, there is evidence that the difference between inclusive and exclusive nationalist identifications has also travelled beyond Europe

Ubiquitous sensorization for multimodal assessment of driving patterns

Sustainability issues and sustainable behaviours are becoming concerns of increasing signi cance in our society. In the case of transportation systems, it would be important to know the impact of a given driving behaviour over sustainability factors. This paper describes a system that integrates ubiquitous mobile sensors available on devices such as smartphones, intelligent wristbands and smartwatches, in order to determine and classify driving patterns and to assess driving e ficiency and driver's moods. It first identi fies the main attributes for contextual information, with relevance to driving analysis. Next, it describes how to obtain that information from ubiquitous mobile sensors, usually carried by drivers. Finally, it addresses the multimodal assessment process which produces the analysis of driving patterns and the classi cation of driving moods, promoting the identifi cation of either regular or aggressive driving patterns, and the classi fication of mood types between aggressive and relaxed. Such an approach enables ubiquitous sensing of personal driving patterns across diff erent vehicles, which can be used in sustainability frameworks, driving alerts and recommendation systems.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012). It is also supported by a doctoral grant, SFRH/BD/78713/2011, issued by FCT in Portugal

Seasonal, synoptic, and diurnal-scale variability of biogeochemical trace gases and O2 from a 300-m tall tower in central Siberia

We present first results from 19 months of semicontinuous concentration measurements of biogeochemical trace gases (CO2, CO, and CH4) and O2, measured at the Zotino Tall Tower Observatory (ZOTTO) in the boreal forest of central Siberia. We estimated CO2 and O2 seasonal cycle amplitudes of 26.6 ppm and 134 per meg, respectively. An observed west-east gradient of about -7 ppm (in July 2006) between Shetland Islands, Scotland, and ZOTTO reflects summertime continental uptake of CO2 and is consistent with regional modeling studies. We found the oceanic component of the O2 seasonal amplitude (Atmospheric Potential Oxygen, or APO) to be 51 per meg, significantly smaller than the 95 per meg observed at Shetlands, illustrating a strong attenuation of the oceanic O2 signal in the continental interior. Comparison with the Tracer Model 3 (TM3) atmospheric transport model showed good agreement with the observed phasing and seasonal amplitude in CO2; however, the model exhibited greater O2 (43 per meg, 32%) and smaller APO (9 per meg, 18%) amplitudes. This seeming inconsistency in model comparisons between O2 and APO appears to be the result of phasing differences in land and ocean signals observed at ZOTTO, where ocean signals have a significant lag. In the first 2 months of measurements on the fully constructed tower (November and December 2006), we observed several events with clear vertical concentration gradients in all measured species except CO. During “cold events” (below -30°C) in November 2006, we observed large vertical gradients in CO2 (up to 22 ppm), suggesting a strong local source. The same pattern was observed in CH4 concentrations for the same events. Diurnal vertical CO2 gradients in April to May 2007 gave estimates for average nighttime respiration fluxes of 0.04 ± 0.02 mol C m-2 d-1, consistent with earlier eddy covariance measurements in 1999–2000 in the vicinity of the tower