Geo-temporal Twitter demographics

This paper seeks and uses highly disaggregate social media sources to characterize Greater London in terms of flows of people with modelled individual characteristics, as well as conventional measures of land use morphology and night-time residence. We conduct three analyses. First, we use the Shannon Entropy measure to characterize the geography of information creation across the city. Second, we create a geo-temporal demographic classification of Twitter users in London. Third, we begin to use Twitter data to characterize the links between different locations across the city. We see all three elements as data rich, highly disaggregate geo-temporal analysis of urban form and function, albeit one that pertains to no clearly defined population. Our conclusions reflect upon this severe shortcoming in analysis using social media data, and its implications for progressing our understanding of socio-spatial distributions within cities.     

Satellite and ground-based remote sensing of aerosols during intense haze event of October 2013 over lahore,Pakistan

Due to increase in population and economic development, the mega-cities are facing increased haze events which are causing important effects on the regional environment and climate. In order to understand these effects, we require an in-depth knowledge of optical and physical properties of aerosols in intense haze conditions. In this paper an effort has been made to analyze the microphysical and optical properties of aerosols during intense haze event over mega-city of Lahore by using remote sensing data obtained from satellites (Terra/Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)) and ground based instrument (AErosol RObotic NETwork (AERONET)) during 6-14 October 2013. The instantaneous highest value of Aerosol Optical Depth (AOD) is observed to be 3.70 on 9 October 2013 followed by 3.12 on 8 October 2013. The primary cause of such high values is large scale crop residue burning and urban-industrial emissions in the study region. AERONET observations show daily mean AOD of 2.36 which is eight times higher than the observed values on normal day. The observed fine mode volume concentration is more than 1.5 times greater than the coarse mode volume concentration on the high aerosol burden day. We also find high values (~0.95) of Single Scattering Albedo (SSA) on 9 October 2013. Scatter-plot between AOD (500 nm) and Angstrom exponent (440-870 nm) reveals that biomass burning/urban-industrial aerosols are the dominant aerosol type on the heavy aerosol loading day over Lahore. MODIS fire activity image suggests that the areas in the southeast of Lahore across the border with India are dominated by biomass burning activities. A Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model backward trajectory showed that the winds at 1000 m above the ground are responsible for transport from southeast region of biomass burning to Lahore. CALIPSO derived sub-types of aerosols with vertical profile taken on 10 October 2013 segregates the wide spread aerosol burden as smoke, polluted continental and dust aerosols.     

Mapping soil electric conductivity using Bayesian kriging: A case study from Qasur,Pakistan

Quality of soil data is vital to formulate agricultural policies at different scales. Current agricultural applications in Pakistan depend however, on average values of soil estimates over larger areas. In this work, model-based ordinary kriging (OK) and Bayesian kriging (BK) to interpolate soil data is used. The aim is to compare the two different methods for the accuracy of soil data prediction. For this soils were sampled for Electrical Conductivity (EC, dS m ^–1) at 759 different locations in the rural agricultural areas of Qasur Tehsil, Pakistan. Cross validation was used to compare the performance of OK and BK. Our results show strong skewness and spatial dependency of soil EC values in heterogeneous regions. Box-Cox transformation successfully reduced the level of skewness in the soil EC data (from 14.1 to 0.11). Contrary to OK, under-estimation of soil EC values was not evident in the BK interpolation. Mean square prediction error for BK (1.45) was significantly reduced as compared to that for OK (6.1). Considering these findings, BK is a better model to explain the sub-regional soil EC variability and estimating strategies for sustainable agricultural planning in Pakistan.     

Emission quantification of refrigerant CFCs,HCFCs and HFCs in megacity Lahore (Pakistan) and contributed ODPs and GWPs

An integrated assessment of emissions of some important refrigerant ozone depleting substances (ODSs) (CFC-11, CFC-12, HCFC-141b and HFC-134a) and their contributed ozone depletion potentials (ODPs) and global warming potentials (GWPs) have been made in the megacity Lahore (Pakistan) for the period from 2005 to 2013. During the production of 6.488 million refrigerator units, the cumulative estimated emissions of CFC-11, CFC-12, HCFC-141b and HFC-134a were 129.7, 6.8, 1257 and 104 mega grams (1 Mg = 10⁶ grams). The estimated GWP (CO₂-eq) and ODP (CFC 11-eq) associated with production phase emissions of these four gases were 616.07, 73.52, 910.96, and 87.36 kilotonnes, and 129.7, 6.8, 139.4, and 0 tonnes, respectively. ODP of HFC-134a is considered to be zero. In addition, the repair and maintenance of 81.2 thousand units resulted in 10.8 Mg emissions of CFC-12 with 10.8 tonnes ODP(CFC 11-eq) and 117,802 tonnes GWP (CO₂-eq) that were higher than the HFC-134a emissions recorded at 4.3 Mg causing 4563 tonnes GWP(CO₂-eq). A decrease in ODP (CFC 11-eq) and GWP (CO₂-eq) at the rate of ?8.3% and ?8.2% per year is observed to be contributed by all the selected ODSs during the study period.