scholarly journals Mapping current and future European public water withdrawals and consumption

2014 ◽  
Vol 18 (2) ◽  
pp. 407-416 ◽  
Author(s):  
I. Vandecasteele ◽  
A. Bianchi ◽  
F. Batista e Silva ◽  
C. Lavalle ◽  
O. Batelaan
Keyword(s):  
Population Density ◽  
Temporal Trends ◽  
Absolute Error ◽  
Reference Scenario ◽  
Total Water ◽  
Country Level ◽  
European Public ◽  
Density Map ◽  
Per Capita ◽  
Water Withdrawals

Abstract. In Europe, public water withdrawals make up on average 30% and in some cases up to 60% of total water withdrawals. These withdrawals are becoming increasingly important with growing population density; hence there is a need to understand the spatial and temporal trends involved. Pan-European public/municipal water withdrawals and consumption were mapped for 2006 and forecasted for 2030. Population and tourism density were assumed to be the main driving factors for withdrawals. Country-level statistics on public water withdrawals were disaggregated to a combined population and tourism density map (the "user" density map) computed for 2006. The methodology was validated using actual regional withdrawal statistics from France for 2006. The total absolute error (TAE) calculated was proven to be reduced by taking into account the tourism density in addition to the population density. In order to forecast the map to 2030 we considered a reference scenario where per capita withdrawals were kept constant in time. Although there are large variations from region to region, this resulted in a European average increase of water withdrawals of 16%. If we extrapolate the average reduction in per capita withdrawals seen between 2000 and 2008, we forecast a reduction in average total water withdrawals of 4%. Considering a scenario where all countries converge to an optimal water use efficiency, we see an average decrease of 28%.

scholarly journals Mapping current and future European public water withdrawals and consumption

2013 ◽  
Vol 10 (7) ◽  
pp. 9889-9914 ◽  
Author(s):  
I. Vandecasteele ◽  
A. Bianchi ◽  
F. Batista e Silva ◽  
C. Lavalle ◽  
O. Batelaan
Keyword(s):  
Population Density ◽  
Temporal Trends ◽  
Absolute Error ◽  
Maximal Increase ◽  
Country Level ◽  
European Public ◽  
Level Statistics ◽  
Density Map ◽  
Water Withdrawals ◽  
Spatial And Temporal Trends

Abstract. In Europe, public water withdrawals make up on average 30%, and in some cases up to 60% of total water withdrawals. These withdrawals are becoming increasingly important with growing population density; hence there is a need to understand the spatial and temporal trends involved. Pan-European public/municipal water withdrawals and consumption were mapped for 2006 and forecasted for 2030. Population and tourism density were assumed to be the main driving factors for withdrawals. Country-level statistics on public water withdrawals were disaggregated to a combined population and tourism density map (the "user" density map) computed for 2006. In order to forecast the map to 2030 we assumed the water withdrawals per user to remain constant in time, so that the future withdrawals reflected the projected population and tourism trends. The methodology was validated using actual regional withdrawal statistics from France for 2006. The Total Absolute Error (TAE) calculated was proven to be reduced by taking into account the tourism density in addition to the population density. Our results show that although there are large variations from region to region, in general public water withdrawals will increase significantly over the period 2006 to 2030. The European average increase is 16%, with a maximal increase of 53% in Ireland.

scholarly journals Improvement of a Dasymetric Method for Implementing Sustainable Development Goal 11 Indicators at an Intra-Urban Scale

2021 ◽  
Vol 13 (14) ◽  
pp. 2835
Author(s):  
Mariella Aquilino ◽  
Maria Adamo ◽  
Palma Blonda ◽  
Angela Barbanente ◽  
Cristina Tarantino
Keyword(s):  
Sustainable Development ◽  
Population Density ◽  
Absolute Error ◽  
Specific Weight ◽  
Sustainable Development Goal ◽  
Development Goal ◽  
Density Map ◽  
The Mean ◽  
Regional Authorities ◽  
Basic Input

Local and Regional Authorities require indicators at the intra-urban scale to design adequate policies to foster the achievement of the objectives of Sustainable Development Goal (SDG) 11. Updated high-resolution population density and settlement maps are the basic input products for such indicators and their sub-indicators. When provided at the intra-urban scale, these essential variables can facilitate the extraction of population flows, including both local and regular migrant components. This paper discusses a modification of the dasymetric method implemented in our previous work, aimed at improving the population density estimation. The novelties of our paper include the introduction of building height information and site-specific weight values for population density correction. Based on the proposed improvements, selected indicators/sub-indicators of four SDG 11 targets were updated or newly implemented. The output density map error values are provided in terms of the mean absolute error, root mean square error and mean absolute percentage indicators. The values obtained (i.e., 2.3 and 4.1 people, and 8.6%, respectively) were lower than those of the previous dasymetric method. The findings suggest that the new methodology can provide updated information about population fluxes and processes occurring over the period 2011–2020 in the study site—Bari city in southern Italy.

Classification Method of Population Density Map Based on Lorenz Curve

2010 ◽  
Vol 11 (6) ◽  
pp. 833-838 ◽  
Author(s):  
Jiafu HAN ◽  
Hongsheng LI ◽  
Zhong ZHANG
Keyword(s):  
Population Density ◽  
Lorenz Curve ◽  
Classification Method ◽  
Density Map

scholarly journals Contribution of ICOH to Address the Different OSH Needs among Countries: Results of a Survey

2021 ◽  
Vol 18 (9) ◽  
pp. 4665
Author(s):  
Bruna Rondinone ◽  
Antonio Valenti ◽  
Valeria Boccuni ◽  
Erika Cannone ◽  
Pierluca Dionisi ◽  
...  
Keyword(s):  
Occupational Safety ◽  
Multidisciplinary Approach ◽  
Multiple Correspondence Analysis ◽  
Gdp Per Capita ◽  
Online Questionnaire ◽  
Research Education ◽  
Country Level ◽  
Safety And Health ◽  
Per Capita ◽  
And Training

The aim of this study is to map the coverage of occupational safety and health (OSH) rules and provisions and their enforcement at a country level worldwide. Members’ participation in the International Commission on Occupational Health (ICOH) activities was also investigated. We used a questionnaire-based survey to collect data. An online questionnaire was administered from February 14 to March 18, 2018 to all ICOH members for the triennium 2015 to 2017 (n = 1929). We received 384 completed questionnaires from 79 countries, with a 20% response rate. To synthesize information about the coverage of OSH rules and provisions and their level of enforcement, a synthetic coverage index was calculated and combined with country, gross domestic product (GDP) per capita and the human development index (HDI). We used multiple correspondence analysis (MCA) to analyze the members’ participation in ICOH activities. More than 90.0% of the sample declared that in their own country there is a set of rules and provisions regulating OSH in the workplace, and training procedures and tools to improve workers’ awareness. However, these rules and training procedures are mainly “partially” enforced and utilized (39.0% and 45.4%). There was no statistically significant association between country and GDP per capita and the synthetic coverage index, whilst controlling for HDI. The level of engagement in ICOH activities is higher in senior members (aged 65 years or older), coming from high-income countries, having held a position within ICOH, with a higher level of education and a researcher position. An integrated and multidisciplinary approach, which includes research, education and training, is needed to address OSH issues and their impact both at global and country level.

scholarly journals COVID-19 Mortality Rate and Its Incidence in Latin America: Dependence on Demographic and Economic Variables

2021 ◽  
Vol 18 (13) ◽  
pp. 6900
Author(s):  
Javier Cifuentes-Faura
Keyword(s):  
Latin America ◽  
Mortality Rate ◽  
Population Density ◽  
Life Expectancy ◽  
Latin American ◽  
Positive Influence ◽  
Death Rates ◽  
Per Capita ◽  
Latin American Countries ◽  
Quality Infrastructure

The pandemic caused by COVID-19 has left millions infected and dead around the world, with Latin America being one of the most affected areas. In this work, we have sought to determine, by means of a multiple regression analysis and a study of correlations, the influence of population density, life expectancy, and proportion of the population in vulnerable employment, together with GDP per capita, on the mortality rate due to COVID-19 in Latin American countries. The results indicated that countries with higher population density had lower numbers of deaths. Population in vulnerable employment and GDP showed a positive influence, while life expectancy did not appear to significantly affect the number of COVID-19 deaths. In addition, the influence of these variables on the number of confirmed cases of COVID-19 was analyzed. It can be concluded that the lack of resources can be a major burden for the vulnerable population in combating COVID-19 and that population density can ensure better designed institutions and quality infrastructure to achieve social distancing and, together with effective measures, lower death rates.

Impact of urbanization on per capita energy use and emissions in India

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Stuti Haldar ◽  
Gautam Sharma
Keyword(s):  
Carbon Dioxide ◽  
Energy Consumption ◽  
Population Density ◽  
Carbon Dioxide Emissions ◽  
Energy Demand ◽  
Energy Use ◽  
Energy Intensity ◽  
Series Data ◽  
Content Type ◽  
Per Capita

Purpose The purpose of this study is to investigate the impacts of urbanization on per capita energy consumption and emissions in India. Design/methodology/approach The present study analyses the effects of urbanization on energy consumption patterns by using the Stochastic Impacts by Regression on Population, Affluence and Technology in India. Time series data from the period of 1960 to 2015 has been considered for the analysis. Variables including Population, GDP per capita, Energy intensity, share of industry in GDP, share of Services in GDP, total energy use and urbanization from World Bank data sources have been used for investigating the relationship between urbanization, affluence and energy use. Findings Energy demand is positively related to affluence (economic growth). Further the results of the analysis also suggest that, as urbanization, GDP and population are bound to increase in the future, consequently resulting in increased carbon dioxide emissions caused by increased energy demand and consumption. Thus, reducing the energy intensity is key to energy security and lower carbon dioxide emissions for India. Research limitations/implications The study will have important policy implications for India’s energy sector transition toward non- conventional, clean energy sources in the wake of growing share of its population residing in urban spaces. Originality/value There are limited number of studies considering the impacts of population density on per capita energy use. So this study also contributes methodologically by establishing per capita energy use as a function of population density and technology (i.e. growth rates of industrial and service sector).

scholarly journals Regional quality of living in Europe

REGION ◽  
2015 ◽  
Vol 2 (2) ◽  
pp. 1 ◽  
Author(s):  
Piet Lagas ◽  
Frank Van Dongen ◽  
Frank Van Rijn ◽  
Hans Visser
Keyword(s):  
Population Density ◽  
Capital City ◽  
Gdp Per Capita ◽  
European Regions ◽  
Policy Makers ◽  
The North ◽  
City Regions ◽  
Quality Of Living ◽  
Per Capita

This article sets out the conceptual framework and results of Regional Quality of Living indicators that were developed in order to benchmark European NUTS2 regions. Nine non-business-related indicators are constructed to support the goal of policy makers to improve the attractiveness of regions and cities for people or companies to settle in, and by doing so create economic growth. Each of the constructed indicators represents a pillar of the Quality of Living. The highest indicator scores are found for regions within Switzerland, Sweden, Norway and the Netherlands. Some countries show a wide divergence between regional scores. The southern regions of Italy and Spain, for example, have significantly lower scores than those in the north. In addition, capital city regions have better RQI scores. A positive correlation was found between the average RQI scores and both GDP per capita and weighted population density. Compared to GDP per capita, weighted population density has a modest influence on the RQI score. The European regions are divided into 11 clusters, based upon GDP per capita and weighted population density in order to benchmark a region with its peers.

scholarly journals Multiscale Aggregate Networks with Dense Connections for Crowd Counting

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Pengfei Li ◽  
Min Zhang ◽  
Jian Wan ◽  
Ming Jiang
Keyword(s):  
Mean Squared Error ◽  
Absolute Error ◽  
Image Features ◽  
Convolutional Network ◽  
Crowd Counting ◽  
Squared Error ◽  
Crowd Density ◽  
Density Maps ◽  
Density Map ◽  
Map Decoder

The most advanced method for crowd counting uses a fully convolutional network that extracts image features and then generates a crowd density map. However, this process often encounters multiscale and contextual loss problems. To address these problems, we propose a multiscale aggregation network (MANet) that includes a feature extraction encoder (FEE) and a density map decoder (DMD). The FEE uses a cascaded scale pyramid network to extract multiscale features and obtains contextual features through dense connections. The DMD uses deconvolution and fusion operations to generate features containing detailed information. These features can be further converted into high-quality density maps to accurately calculate the number of people in a crowd. An empirical comparison using four mainstream datasets (ShanghaiTech, WorldExpo’10, UCF_CC_50, and SmartCity) shows that the proposed method is more effective in terms of the mean absolute error and mean squared error. The source code is available at https://github.com/lpfworld/MANet.

scholarly journals SARS-COV-2 Vaccines: What Indicators are Associated with the Worldwide Distribution of the First Doses

2021 ◽  
Vol 58 ◽  
pp. 004695802110601
Author(s):  
Marcos Felipe Falcão Sobral ◽  
Brigitte Renata Bezerra de Oliveira ◽  
Ana Iza Gomes da Penha Sobral ◽  
Marcelo Luiz Monteiro Marinho ◽  
Gisleia Benini Duarte ◽  
...  
Keyword(s):  
Population Density ◽  
Life Expectancy ◽  
Human Development ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
The United States ◽  
Gdp Per Capita ◽  
Reproduction Rate ◽  
Worldwide Distribution ◽  
Per Capita

The present study aimed to identify the factors associated with the distribution of the first doses of the COVID-19 vaccine. In this study, we used 9 variables: human development index (HDI), gross domestic product (GDP per capita), Gini index, population density, extreme poverty, life expectancy, COVID cases, COVID deaths, and reproduction rate. The time period was until February 1, 2021. The variable of interest was the sum of the days after the vaccine arrived in the countries. Pearson’s correlation coefficients were calculated, and t-test was performed between the groups that received and did not receive the immunizer, and finally, a stepwise linear regression model was used. 58 (30.4%) of the 191 countries received the SARS-CoV-2 vaccine. The countries that received the most doses were the United States, China, the United Kingdom, and Israel. Vaccine access in days showed a positive Pearson correlation HDI, GDP, life expectancy, COVID-19 cases, deaths, and reproduction rate. Human development level, COVID-19 deaths, GDP per capita, and population density are able to explain almost 50% of the speed of access to immunizers. Countries with higher HDI and per capita income obtained priority access.

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