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A new global anthropogenic heat estimation based on high-resolution nighttime light data.

ABSTRACT: Consumption of fossil fuel resources leads to global warming and climate change. Apart from the negative impact of greenhouse gases on the climate, the increasing emission of anthropogenic heat from energy consumption also brings significant impacts on urban ecosystems and the surface energy balance. The objective of this work is to develop a new method of estimating the global anthropogenic heat budget and validate it on the global scale with a high precision and resolution dataset. A statistical algorithm was applied to estimate the annual mean anthropogenic heat (AH-DMSP) from 1992 to 2010 at 1×1?km2 spatial resolution for the entire planet. AH-DMSP was validated for both provincial and city scales, and results indicate that our dataset performs well at both scales. Compared with other global anthropogenic heat datasets, the AH-DMSP has a higher precision and finer spatial distribution. Although there are some limitations, the AH-DMSP could provide reliable, multi-scale anthropogenic heat information, which could be used for further research on regional or global climate change and urban ecosystems.

SUBMITTER: Yang W

PROVIDER: S-EPMC5667572 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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A new global anthropogenic heat estimation based on high-resolution nighttime light data.

Yang Wangming W Luan Yibo Y Liu Xiaolei X Yu Xiaoyong X Miao Lijuan L Cui Xuefeng X

Scientific data 20170822

Consumption of fossil fuel resources leads to global warming and climate change. Apart from the negative impact of greenhouse gases on the climate, the increasing emission of anthropogenic heat from energy consumption also brings significant impacts on urban ecosystems and the surface energy balance. The objective of this work is to develop a new method of estimating the global anthropogenic heat budget and validate it on the global scale with a high precision and resolution dataset. A statistic ...[more]

PMID: 28829436

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Project description:The novel coronavirus (COVID-19) has induced unprecedented improvements of air quality due to drastic shrinking of human activities during the pandemic lockdown in 2020. While declines of most air pollutants have been globally evidenced in most cities worldwide, there is few detailed spatial knowledge at local scale. Therefore, we present here a high resolution mapping of the 2018-2020 evolution of human activities and air pollutants in Wuhan. Human activities were assessed by nighttime light radiance. We measured the air quality index (AQI) as the maximum value among air quality sub-indices of SO2, NO2, CO, O3 and particulate matter. We also compared mean monthly pollutant concentration during January-April in 2018, 2019 and 2020. Mapping results show that variations of nighttime light radiance were heterogenous at local scale, showing both rises and declines in the same district. The radiance decreased in eight districts located mostly in the city center, as a result of lower human activity, but the radiance increased in the five surrounding districts, as a consequence of people staying at home. AQI was low during lockdown, averaging at 57, but showed strong daily variations with a slight pollution around February 5 with AQI rising to 126. During this pollution event, particulate matter, SO2, NO2 and CO levels were positively correlated, suggesting common sources, but were not correlated with ozone; and particulate matter, SO2, NO2 and CO decreased with relative humidity, suggesting removal by precipitation. Comparison of 2020 data with previous years shows that particulate matter and NO2 were highly reduced, CO was less reduced due to ongoing power industries, SO2 first declined then increased to exceed 2018-19 values due to coal combustion, and ozone levels was more abundant due both to less NOx pollution and the weekend effect.Supplementary informationThe online version contains supplementary material available at 10.1007/s10311-021-01222-x.

Project description:BackgroundThe under-five mortality rate (the probability of dying between birth and age 5 y, also denoted in the literature as U5MR and (5)q(0)) is a key indicator of child health, but it conceals important information about how this mortality is distributed by age. One important distinction is what amount of the under-five mortality occurs below age 1 y ((1)q(0)) versus at age 1 y and above ((4)q(1)). However, in many country settings, this distinction is often difficult to establish because of various types of data errors. As a result, it is common practice to resort to model age patterns to estimate (1)q(0) and (4)q(1) on the basis of an observed value of (5)q(0). The most commonly used model age patterns for this purpose are the Coale and Demeny and the United Nations systems. Since the development of these models, many additional sources of data for under-five mortality have become available, making possible a general evaluation of age patterns of infant and child mortality. In this paper, we do a systematic comparison of empirical values of (1)q(0) and (4)q(1) against model age patterns, and discuss whether observed deviations are due to data errors, or whether they reflect true epidemiological patterns not addressed in existing model life tables.Methods and findingsWe used vital registration data from the Human Mortality Database, sample survey data from the World Fertility Survey and Demographic and Health Surveys programs, and data from Demographic Surveillance Systems. For each of these data sources, we compared empirical combinations of (1)q(0) and (4)q(1) against combinations provided by Coale and Demeny and United Nations model age patterns. We found that, on the whole, empirical values fall relatively well within the range provided by these models, but we also found important exceptions. Sub-Saharan African countries have a tendency to exhibit high values of (4)q(1) relative to (1)q(0), a pattern that appears to arise for the most part from true epidemiological causes. While this pattern is well known in the case of western Africa, we observed that it is more widespread than commonly thought. We also found that the emergence of HIV/AIDS, while perhaps contributing to high relative values of (4)q(1), does not appear to have substantially modified preexisting patterns. We also identified a small number of countries scattered in different parts of the world that exhibit unusually low values of (4)q(1) relative to (1)q(0), a pattern that is not likely to arise merely from data errors. Finally, we illustrate that it is relatively common for populations to experience changes in age patterns of infant and child mortality as they experience a decline in mortality.ConclusionsExisting models do not appear to cover the entire range of epidemiological situations and trajectories. Therefore, model life tables should be used with caution for estimating (1)q(0) and (4)q(1) on the basis of (5)q(0). Moreover, this model-based estimation procedure assumes that the input value of (5)q(0) is correct, which may not always be warranted, especially in the case of survey data. A systematic evaluation of data errors in sample surveys and their impact on age patterns of (1)q(0) and (4)q(1) is urgently needed, along with the development of model age patterns of under-five mortality that would cover a wider range of epidemiological situations and trajectories. Please see later in the article for the Editors' Summary.

Dataset Information

A new global anthropogenic heat estimation based on high-resolution nighttime light data.

Publications

A new global anthropogenic heat estimation based on high-resolution nighttime light data.

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