Cyclability in Lahore, Pakistan. Looking into Potential for Greener Urban Traveling

Measuring perceived or objective cyclability or bikeability has drawn less attention compared to walkability, particularly in developing countries like those in South Asia and the Middle East. This paper presents the results of a survey about cyclability in Lahore, Pakistan, focusing on human perceptions rather than the built environment. The overall sample included a total of 379 respondents from three socio-economic classes: those from lower socioeconomic backgrounds accessing traditional/older bazaars, respondents from the middle socio-economic class accessing uptown bazaars, and respondents of higher socio-economic status accessing pedestrian shopping malls. The exploratory data collection was conducted in spring 2018 in Lahore by means of a short standard questionnaire with 19 questions, resulting in 17 categorical/dummy variables, two openended variables, and two continuous variables targeting socio-economics, bike trip characteristics, biking barriers, and preferred travel specifications. The results showed that the middle socio-economic group was more inclined, flexible, and willing to bike compared to the lower and higher socioeconomic- groups. The lower socio-economic group used the bicycle more frequently than the middle socio-economic group. Around half of the middle socio-economic group commutes via bike compared to the lower socio-economic group. There was little to no representation of 55-64 and 65+ age groups in the data. The descriptive findings of this survey indicate some preliminary signs of differences of decisions and perceptions about biking compared to high-income and European countries. These differences need to be tested in future statistical analyses

Towards net-zero: CO2 capture and biogas purification through electric potential swing desorption to achieve SDGs 7 and 13

Currently, the potential of biomethane derived from biogas is substantial, positioning it to fulfill a considerable share of the United Kingdom’s total energy needs. The primary challenge associated with raw biogas lies in purifying it to produce biomethane, a process that necessitates the removal of carbon dioxide and hydrogen sulfide. Among the various methods, adsorption of activated carbon (AC) stands out as a particularly effective and cost-efficient approach for converting biogas into biomethane, provided that the regeneration of AC proves economically viable. In this research, a segment of activated carbon was utilized to assess the adsorption properties when exposed to a gas mixture of CO2, H2S, and N2 within a regenerative activated carbon setup. This investigation encompassed the analysis of adsorption and desorption behaviors, process capacities, and the impact of regeneration. To enhance the adsorption of CO2, electro-conductive polymers (ECPs) were incorporated into the AC samples, leading to an extension in breakthrough time. Subsequent to adsorption, the electric potential swing desorption (EPSD) was employed for in situ regeneration of activated carbon samples, involving potentials of up to 30 V. The findings exhibited that the newly introduced EPSD technique considerably diminished desorption durations for both H2S and CO2. Moreover, it successfully rejuvenated the accessible adsorption sites, resulting in reduced desorption times compared to the initial breakthrough time during adsorption. Consequently, the EPSD system proves to be a promising candidate for in situ regeneration of activated carbon to eliminate CO2 and H2S from biogas. Notably, this approach offers inherent advantages over conventional methods including thermal swing adsorption (TSA) and pressure swing adsorption (PSA) in terms of regeneration. The demonstrated method underscores the potential for more efficient and economically viable cycles of adsorption and desorption, thereby enhancing the overall biogas-to-biomethane conversion process to achieve SDGs 7 and 13 for clean and green energy applications

Towards net-zero: CO 2 capture and biogas purification through electric potential swing desorption to achieve SDGs 7 and 13

Currently, the potential of biomethane derived from biogas is substantial, positioning it to fulfill a considerable share of the United Kingdom’s total energy needs. The primary challenge associated with raw biogas lies in purifying it to produce biomethane, a process that necessitates the removal of carbon dioxide and hydrogen sulfide. Among the various methods, adsorption of activated carbon (AC) stands out as a particularly effective and cost-efficient approach for converting biogas into biomethane, provided that the regeneration of AC proves economically viable. In this research, a segment of activated carbon was utilized to assess the adsorption properties when exposed to a gas mixture of CO2, H2S, and N2 within a regenerative activated carbon setup. This investigation encompassed the analysis of adsorption and desorption behaviors, process capacities, and the impact of regeneration. To enhance the adsorption of CO2, electro-conductive polymers (ECPs) were incorporated into the AC samples, leading to an extension in breakthrough time. Subsequent to adsorption, the electric potential swing desorption (EPSD) was employed for in situ regeneration of activated carbon samples, involving potentials of up to 30 V. The findings exhibited that the newly introduced EPSD technique considerably diminished desorption durations for both H2S and CO2. Moreover, it successfully rejuvenated the accessible adsorption sites, resulting in reduced desorption times compared to the initial breakthrough time during adsorption. Consequently, the EPSD system proves to be a promising candidate for in situ regeneration of activated carbon to eliminate CO2 and H2S from biogas. Notably, this approach offers inherent advantages over conventional methods including thermal swing adsorption (TSA) and pressure swing adsorption (PSA) in terms of regeneration. The demonstrated method underscores the potential for more efficient and economically viable cycles of adsorption and desorption, thereby enhancing the overall biogas-to-biomethane conversion process to achieve SDGs 7 and 13 for clean and green energy applications

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019

Background Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. Methods We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (USMR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. Findings Global U5MR decreased from 71.2 deaths per 1000 livebirths (95% uncertainty interval WI] 68.3-74-0) in 2000 to 37.1 (33.2-41.7) in 2019 while global NMR correspondingly declined more slowly from 28.0 deaths per 1000 live births (26.8-29-5) in 2000 to 17.9 (16.3-19-8) in 2019. In 2019,136 (67%) of 204 countries had a USMR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030,154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9.65 million (95% UI 9.05-10.30) in 2000 and 5.05 million (4.27-6.02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3.76 million 95% UI 3.53-4.021) in 2000 to 48% (2.42 million; 2.06-2.86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0.80 (95% UI 0.71-0.86) deaths per 1000 livebirths and U5MR to 1.44 (95% UI 1-27-1.58) deaths per 1000 livebirths, and in 2019, there were as many as 1.87 million (95% UI 1-35-2.58; 37% 95% UI 32-43]) of 5.05 million more deaths of children younger than 5 years than the survival potential frontier. Interpretation Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve USMR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

The role of ITS and Other Advanced Communication Technologies in Reducing the Transport Impacts of Disasters

This ethically approved, novel study emphasizes an important aspect of Information and communication flow (ICF) that underpins the transport systems’ activities under disasters (e.g. search, rescue, relief operations and emergency related travel activities). Multi perspectives of ICF, based on numerous ICT and ITS technologies, are investigated in detail by employing various analysis techniques and methods. Two scenarios were developed for three case studies from developed and developing countries (one in UK and two in Pakistan). The effectiveness and choice making process regarding use of ITS technologies by the transport-disaster managers (scenario1) and people affected (scenario 2) were investigated for three phases (pre, during, post) of two different disasters (floods and earthquakes). Participants for both scenarios were recruited and data collected and analysed using different data collection and analysis methods. The study contributes a new data collection and analysis technique named as the Q-Likert methodology, which was developed and used to identify those factors (relating to ITS deployment plans, policies, ICF within and among other authorities and availability of resources, expertise and liberty to practice) that limit the scope of ITS technologies during disasters. An evaluation of the effectiveness of each ITS technology under both scenarios and for three phases of disasters is reported. A range of variables (e.g. personal characteristics of people, prevailing situations and facilities) and their influence on the use of ITS technologies was tested. Many aspects relating to transport-disaster affected communities are revealed. The results are fused and validated through data fusion technique to get maximum information regarding the multidimensional issues of transport-disasters ICF. Based on the evidence found, an integrated framework is proposed covering ITS technologies, transport and disasters systems. The framework focuses on the provision of an un-interrupted ICF along with cooperation, coordination and exchange of information and resources between all stakeholders

Logit and probit models explaining perceived cycling motives, barriers, and biking trip generation in Lahore, Pakistan

Cycling as an attractive mode of transport is a challenge, especially in developing countries like Pakistan. Previous research on cycling in developing countries is insufficient to answer that how people can be encouraged to bike in different regions and cultures. This research, therefore, directs two research questions based on the perceptions of the people of Lahore. The first research question addresses the perceived motives of everyday biking trip generation and the second question addresses the perceived barriers in biking in the city of Lahore. The data sample of 379 subjects was collected through self-reported questionnaire across different socioeconomic groups. The questionnaire was designed to discuss the motives for biking such as affordability, reliability, and accessibility as well as to identify the barriers such as cultural issues, gender problems and non-availability of infrastructure for biking. Along with descriptive statistics, Multinomial Logistic was used to analyze perceived motives, Binary Logistic for perceived barriers and Ordinal Probit for biking trip generation. The obtained results are very interesting and provide various insights about the perceptions of people regarding biking trip generation, motives, and barriers with various factors involved. The results are beneficial to urban developers, city planners, transport planners, policy makers and other stakeholders. &nbsp

Logistic models explaining the determinants of biking for commute and non-commute trips in Lahore, Pakistan

The determinants of biking behaviour are less studied in a wide range of developing countries including South Asia. This study takes Lahore, Pakistan as a case-study city to explore the factors defining commute and non-commute bike trips as well as commuting by bike. These issues were analysed by collecting data from 379 subjects accommodating in three socio-economic statuses (lower, medium, and higher) in Lahore in spring 2018. The data were analysed by applying multinomial logistic regression for investigating biking frequency and binomial logistic regression for examining commuting by bike. The results show that gender, age, education, income, purpose of majority of trips, preferred distance to travel using cycle, preferred time to travel using cycle, and preferred bike trip purpose are significantly correlated with biking frequency. The significant determinants of bicycle commuting included categories of education, the purpose of the majority of trips, using bike in combination with other modes, preferred distance to bike, preferred biking time, and preferred bike trip purpose are associated with bicycle commuting. Commuting by bike is more popular in socio-economically weaker neighbourhoods. The discussion of this study shows that the determinants of biking in the sample in Lahore are different from those that have already been addressed by studies undertaken in high-income countries. &nbsp

Cyclability in Lahore, Pakistan: Looking into Potential for Greener Urban Traveling

Measuring perceived or objective cyclability or bikeability has drawn less attention compared to walkability, particularly in developing countries like those in South Asia and the Middle East. This paper presents the results of a survey about cyclability in Lahore, Pakistan, focusing on human perceptions rather than the built environment. The overall sample included a total of 379 respondents from three socio-economic classes: those from lower socio-economic backgrounds accessing traditional/older bazaars, respondents from the middle socio-economic class accessing uptown bazaars, and respondents of higher socio-economic status accessing pedestrian shopping malls. The exploratory data collection was conducted in spring 2018 in Lahore by means of a short standard questionnaire with 19 questions, resulting in 17 categorical/dummy variables, two open-ended variables, and two continuous variables targeting socio-economics, bike trip characteristics, biking barriers, and preferred travel specifications. The results showed that the middle socio-economic group was more inclined, flexible, and willing to bike compared to the lower and higher socio-economic-groups. The lower socio-economic group used the bicycle more frequently than the middle socio-economic group. Around half of the middle socio-economic group commutes via bike compared to the lower socio-economic group. There was little to no representation of 55-64 and 65+ age groups in the data. The descriptive findings of this survey indicate some preliminary signs of differences of decisions and perceptions about biking compared to high-income and European countries. These differences need to be tested in future statistical analyses