PMID- 34648842
OWN - NLM
STAT- MEDLINE
DCOM- 20211125
LR  - 20211125
IS  - 1873-6424 (Electronic)
IS  - 0269-7491 (Linking)
VI  - 292
IP  - Pt A
DP  - 2022 Jan 1
TI  - Appraising regional anthropogenic heat flux using high spatial resolution NTL and 
      POI data: A case study in the Beijing-Tianjin-Hebei region, China.
PG  - 118359
LID - S0269-7491(21)01941-2 [pii]
LID - 10.1016/j.envpol.2021.118359 [doi]
AB  - Rapid urbanization and the aggregation of human activities in cities have 
      resulted in large amounts of anthropogenic heat (AH) emission, which affects 
      urban climate. Quantifying and assessing the AH emission values accurately and 
      analyzing their spatial distribution characteristics is important to understand 
      the energy exchange processes of urban areas. In this study, the high spatial 
      resolution anthropogenic heat flux (AHF) quantification and spatial distribution 
      analysis were conducted using multi-source data in the Beijing-Tianjin-Hebei 
      region (BTH region) of China. First, the AH emission in district and city level 
      were estimated using inventory method based on energy consumption and 
      socio-economic statistical data; Then, AHF spatial quantification models were 
      constructed based on high spatial resolution nighttime light (NTL) data and Point 
      of interests (POI) data, and 130 m x 130 m gridded AHF quantification result in 
      BTH region was realized; Finally, the potential numerical and spatial 
      distribution patterns of AHF were analyzed using various indicators including 
      contribution rate and aggregation index. The results show that: (1) The 
      parameterized index constructed based on NTL and POI data shows a strong 
      correlation with AHF, with R(2) ranging from 0.79 to 0.94 and a mean absolute 
      error (MAE) value of 0.72 w.m(-2), which can be applied to the quantification of 
      gridded AHF values with high resolution. The highest total AHF in the study area 
      is 214 w.m(-2), and the average value is 2.24 w.m(-2). (2) Considering the 
      sources of AHF, industrial emission sources in BTH region contribute the most to 
      the total AHF, but commercial building emission sources in Beijing have a higher 
      contribution, which can reach 33.8%. (3) Different types of AHF have different 
      spatial aggregation levels. Commercial building emission and human metabolic 
      emission have the highest aggregation level, and transportation emission has the 
      lowest aggregation level.
CI  - Copyright (c) 2021 Elsevier Ltd. All rights reserved.
FAU - Wang, Yichen
AU  - Wang Y
AD  - College of Resource Environment and Tourism, Capital Normal University, Beijing, 
      100048, China; Key Laboratory of 3D Information Acquisition and Application, 
      Ministry of Education, Beijing, 100048, China.
FAU - Hu, Deyong
AU  - Hu D
AD  - College of Resource Environment and Tourism, Capital Normal University, Beijing, 
      100048, China; Key Laboratory of 3D Information Acquisition and Application, 
      Ministry of Education, Beijing, 100048, China. Electronic address: 
      deyonghu@cnu.edu.cn.
FAU - Yu, Chen
AU  - Yu C
AD  - College of Resource Environment and Tourism, Capital Normal University, Beijing, 
      100048, China; Key Laboratory of 3D Information Acquisition and Application, 
      Ministry of Education, Beijing, 100048, China.
FAU - Di, Yufei
AU  - Di Y
AD  - College of Resource Environment and Tourism, Capital Normal University, Beijing, 
      100048, China; Key Laboratory of 3D Information Acquisition and Application, 
      Ministry of Education, Beijing, 100048, China.
FAU - Wang, Shasha
AU  - Wang S
AD  - Jiangsu Provincial Key Laboratory of Geographic Information Science and 
      Technology, International Institute for Earth System Science, Nanjing University, 
      Nanjing, Jiangsu, 210023, China.
FAU - Liu, Manqing
AU  - Liu M
AD  - State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, 
      Beijing Normal University, Beijing, 100875, China.
LA  - eng
PT  - Journal Article
DEP - 20211011
PL  - England
TA  - Environ Pollut
JT  - Environmental pollution (Barking, Essex : 1987)
JID - 8804476
RN  - 0 (Air Pollutants)
RN  - 0 (Particulate Matter)
SB  - IM
MH  - *Air Pollutants/analysis
MH  - *Air Pollution/analysis
MH  - Beijing
MH  - China
MH  - Cities
MH  - Environmental Monitoring
MH  - Hot Temperature
MH  - Humans
MH  - Particulate Matter/analysis
OTO - NOTNLM
OT  - Anthropogenic heat flux
OT  - Beijing-Tianjin-Hebei region
OT  - High spatial resolution
OT  - Luojia 1-01
OT  - POI
EDAT- 2021/10/15 06:00
MHDA- 2021/11/26 06:00
CRDT- 2021/10/14 20:12
PHST- 2021/06/03 00:00 [received]
PHST- 2021/10/08 00:00 [revised]
PHST- 2021/10/10 00:00 [accepted]
PHST- 2021/10/15 06:00 [pubmed]
PHST- 2021/11/26 06:00 [medline]
PHST- 2021/10/14 20:12 [entrez]
AID - S0269-7491(21)01941-2 [pii]
AID - 10.1016/j.envpol.2021.118359 [doi]
PST - ppublish
SO  - Environ Pollut. 2022 Jan 1;292(Pt A):118359. doi: 10.1016/j.envpol.2021.118359. 
      Epub 2021 Oct 11.