Academic buildings are the main gathering places in universities and colleges. The crowd flow could cause a change in environmental parameters of buildings. In other words, the change in environmental parameters in buildings can be somewhat reflective of the crowd flow. Therefore, field measurements of the crowd flow and environmental parameters in an academic building at a university were conducted in this study. During the periods of 7:30–8:00 and 13:20–13:50, the average speed of the crowd was the highest, which was about 1.2 m/s; the CO2 concentration was low, which was about 750 ppm. In the periods of 9:20–9:50 and 15:10–15:40, the average speed of people walking in the opposite directions was the lowest, which is 0.42 m/s; however, the CO2 concentration could reach 1800 ppm. Test results showed that the variations of CO2 concentrations were inversely related to the average speed of the crowd in the evacuation passage, except for the periods of 7:30–8:00 and 13:20–13:50. Spatial separation and physical separation could be used in the management of personnel flow in the academic building. The results may provide reference for the management of the crowd flow in similar academic buildings of other universities.
KouBMWeiWZhangRF.Modeling and evaluating emergency evacuation strategy for student residential hall. Math Pract Theor2014;
44: 1–6.
2.
DuanPFXiongSWYangCHZhangHHLiuMF.Personalized route planning system based on Wardrop equilibrium model for pedestrian–vehicle mixed evacuation in campus. JISA2016;
31: 14–22.
3.
ZhangJHZhaoQPanXZouSQ.Research on progress of injury caused by crowded stampede. Chin J Disaster Med2015;
3: 112–115.
4.
ZhouJKZhaoSZengQJ. Statistics of casualties and causes of crowded stampedes from 2001 to 2010. In: The 17th world academic conference on disaster and emergency medicine and the 14th national academic conference on emergency medicine, Beijing, May 31–June 2 2011, paper pp.335–339.
5.
LiuSLiuCWuXQChenD.Causation analysis of stampede accidents on primary and middle school campus based on the FTA-AHP method. Saf Environ Eng2018;
25: 139–145.
6.
ShangRXZhangPHZhongMH.Investigation and analysis on evacuation behavior of large scale population in campus. Procedia Eng2013;
52: 302–308.
7.
DelceaCCotfasLA.Increasing awareness in classroom evacuation situations using agent-based modeling. Physica A2019;
523: 1400–1418.
8.
LiuRJJiangDFShiL.Agent-based simulation of alternative classroom evacuation scenarios. FOAR2016;
5: 111–125.
9.
YangLZRaoPZhuKJLiuSBZhanX.Observation study of pedestrian flow on staircases with different dimensions under normal and emergency conditions. Saf Sci2012;
50: 1173–1179.
10.
HoogendoornSPDaamenW.Pedestrian behavior at bottlenecks. Transport Sci2005;
39: 147–159.
11.
BurghardtSSeyfriedAKlingschW.Performance of stairs-fundamental diagram and topographical measurements. Transport Res Part C: Emerg Technol2013;
37: 268–278.
12.
HoogendoornSDaamenW.Self-organization in pedestrian flow traffic and granular flow’03. Berlin: Springer, 2005, pp.373–382.
13.
FarkasIHelbingDVicsekT.Social behaviour: Mexican waves in an excitable medium. Nature2002;
419: 131–132.
14.
HelbingDJohanssonAAl-AbideenHZ.Dynamics of crowd disasters: an empirical study. Phys Rev E Stat Nonlin Soft Matter Phys2007;
75: 046109.
15.
JelićAAppert-RollandCLemercierSPettréJ.Properties of pedestrians walking in line: fundamental diagrams. Phys Rev E Stat Nonlin Soft Matter Phys2012;
85: 036111.
16.
LiuXSongWGZhangJ.Extraction and quantitative analysis of microscopic evacuation characteristics based on digital image processing. Phys A: Stat Mech Appl2009;
388: 2717–2726.
17.
BoltesMSeyfriedASteffenBSchadschneiderA.Automatic extraction of pedestrian trajectories from video recordings. In: WWFKlingschCRogschASchadschneider, et al. (eds) Pedestrian and evacuation dynamics 2008.
Berlin:
Springer, 2010, pp.43–54.
18.
SeyfriedASteffenBKlingschWBoltesM.The fundamental diagram of pedestrian movement revisited. J Stat Mech: Theory Exp2005;
10: 10002–10014.
19.
LiaoWCSeyfriedAZhangJBoltesM.Experimental study on pedestrian flow through wide bottleneck. Transport Res Proc2014;
2: 26–33.
20.
HuoFZSongWGChenLLiuCLiewKM.Experimental study on characteristics of pedestrian evacuation on stairs in a high-rise building. Saf Sci2016;
86: 165–173.
21.
ZhangJKlingschWSchadschneiderASeyfriedA.Transitions in pedestrian fundamental diagrams of straight corridors and T-junctions. J Stat Mech 2011; P06004: 1–17.
22.
LianLPMaiXSongWGKwokKRRuiYJinS.Pedestrian merging behavior analysis: an experimental study. Fire Saf J2017;
91: 918–925.
23.
LianLPSongWGKwokKRLucianoT.Investigating the time evolution of some parameters describing inflow processes of pedestrians in a room. Physica A2018;
507: 77–88.
24.
LianLPSongWGKwokKRLucianoT.Analysis of repulsion states among pedestrians inflowing into a room. Phys Lett A2018;
382: 2424–2430.
25.
Latoski SP, Dunn WM, Wagenblast B, Randall J and Walker MD. Managing travel for planned special events. Report for U.S. Department of Transportation. Report No. FHWA-OP-04-101, Washington, D.C. US, September 2003.
26.
Federal Emergency Management Agency (FEMA). Special events contingency planning.
Washington DC:
FEMA, 2002.
27.
ChiLBLiFJZhangZD. The method and emphases of large palaestra mass traffic organizing plan. In: Annual meeting of urban transportation planning in China, Beijing, China, December 1–2 2005; pp.335–339.
28.
ShiJG.Research on pedestrian traffic characteristics in special events. PhD Thesis, Beijing University of Technology, Beijing, China, 2007.
29.
RamachandranGAdgateJLBanerjeeSChurchTRJonesDFredricksonASextonK.Indoor air quality in two urban elementary schools – measurements of airborne fungi, carpet allergens, CO2, temperature, and relative humidity. JOEH2005;
2: 553–566.
30.
SantamourisMSynnefaAAsssimakopoulosMLivadaIPavlouKPapaglastraMGaitaniNKolokotsaDAssimakopoulosV.Experimental investigation of the air flow and indoor carbon dioxide concentration in classrooms with intermittent natural ventilation. Energy Build2008;
40: 1833–1843.
31.
ZhaoYJZhangZHJiCFLiuLZhangBHuanC.Characterization of particulate matter from heating and cooling several edible oils. Build Environ2019;
152: 204–213.
32.
ZhangXJWargockiPLianZW.Human responses to carbon dioxide, a follow-up study at recommended exposure limits in non-industrial environments. Build Environ2016;
100: 162–171.
33.
ZhangXJWargockiPLianZW.Physiological responses during exposure to carbon dioxide and bioeffluents at levels typically occurring indoors. Indoor Air2016;
27: 65–77.
34.
MendellMJ.Impact of CO2 on human decision making and productivity. J Appl Soc Psychol2011;
23: 847–866.
35.
CuiWLCaoGGParkJHOuyangQZhuYX.Influence of indoor air temperature on human thermal comfort, motivation and performance. Build Environ2013;
68: 114–122.
36.
JiangJWangDJLiuYFXuYCLiuJP.A study on pupils' learning performance and thermal comfort of primary schools in China. Build Environ2018;
134: 102–113.
37.
JiangJ.Research on classroom thermal environment under the comprehensive impact of thermal comfort and learning performance during winter in rural areas of northwest China. PhD Thesis, Xi'an University of Architectural Science and Technology, Xi’an, China, 2018.
38.
KimJParkSKimHMyoungSY.Emission characterization of size-resolved particles in a pre-school classroom in relation to children’s activities. Indoor Built Environ2019;
28: 659–676.
39.
NiemeläRHannulaMRautioSReijulaKRailioJ.The effect of air temperature on labour productivity in call centres – a case study. Energy Build2002;
34: 759–764.
40.
ShendellDGPrillRFiskWJApteMGBlakeDFaulknerD.Associations between classroom CO2 concentrations and student attendance in Washington and Idaho. Indoor Air2004;
14: 333–341.
41.
LanL.Mechanism and evaluation of the effects of indoor environmental quality on human productivity. PhD Thesis, Shanghai Jiaotong University, Shanghai, China, 2010.
42.
LiW.Combined effects of indoor temperature and noise on human performance. MA Thesis, Zhejiang Sci-tech University, Hangzhou, China, 2013.
43.
WeiP.Energy consumption simulation and energy conservation research on air-conditioning system of the large market in Xi’an city. MA Thesis, Xi'an University of Architectural Science and Technology, Xi’an, China, 2012.
44.
FanJR.Research on adjust to operational air conditioning system with mutative occupant density at the mall. MA Thesis, Guangzhou University, Guangzhou, China, 2017.
45.
GaoRWangCLiAGYuSRDengBS.A novel targeted personalized ventilation system based on the shooting concept. Build Environ2018;
135: 269–279.
46.
GaoRLiuKKLiAGFangZYYangZGCongBH.Biomimetic duct tee for reducing the local resistance of a ventilation and air-conditioning system. Build Environ2018;
129: 130–141.
47.
HolmanJP.Experimental methods for engineers.
New York:
McGraw Hill, 2012.
48.
MoffatRJ.Describing the uncertainties in experimental results. Exp Therm Fluid Sci1988;
1: 3–17.
