A Systematic Review of Indoor Environmental Quality in Passenger Transport Vehicles of Tropical and Subtropical Regions
Abstract
:1. Introduction
2. Materials and Methods
2.1. Search Protocol and Strategy
2.2. Inclusion and Exclusion Criteria
3. Results
3.1. Visualization of Results
Authors | Title | Year | Study Location | Vehicle Type | Method | IEQ Parameters | Occupant | Ventilation | Standard | Main Findings |
---|---|---|---|---|---|---|---|---|---|---|
[44] | In-cabin Particulate Matter Exposure of Heavy Earth Moving Machinery Operators in Indian Opencast Coal Mine | 2024 | India | 3 Heavy earth moving machinery (HEMM): dumper, shovel, and drill | Real-time Experimental measurements | The study measured IAQ parameters: PM10, PM2.5, and PM1. | Driver | Air-conditioning with internal circulation (AC + IC) and non-air-conditioned (NAC) | NA | The study found that in-cabin PM exposure was highest in drills (1992 μg/m3), followed by shovels and dumpers (600–650 μg/m3). HEMM type influenced exposure, with AC cabins reducing in-cabin PM levels by approximately 50% and lowering operator exposure by 21%. |
[45] | In-car occupants’ exposure to airborne fine particles under different ventilation settings: Practical implications | 2024 | Singapore | Sedan car | Real-time Experimental and CFD | The study measured IAQ parameters: CO2 (ppm), PM2.5, Ta, RH, Air Speed | Driver | window open (WO), Windows closed (WC) + AC-IC and WC+ air-conditioning | NA | The study found AC-IC and AC-EC settings reduced PM2.5 levels by 67% and 56%, respectively, compared to NV mode. Open windows increased exposure, while hybrid AC with closed windows minimized it. Back passengers faced higher PM2.5 in AC + WO settings. |
[46] | Air Pollution Inside Vehicles: Making a Bad Situation Worse | 2023 | Thailand | Sedan (4-door) and Pickup trucks (2-door and 4-door). | Real-time Experimental measurements | IAQ Measured: PM2.5 | Driver | Four conditions of WC and WO in dynamic and stationary with Fan and AC for all conditions. | WHO, AQG, Thailand. | The findings revealed mean PM2.5 levels were higher for front seats (72 μg/m3) than for back seats (49 μg/m3). Levels peaked at 124.5 μg/m3 during WC and stationary mode, exceeding applied standards. High PM2.5 exposure highlights the need to limit in-vehicle smoking to reduce second-hand smoke (SHS) risks. |
[47] | In-vehicle and pedestrian exposure to carbon monoxide and volatile organic compounds in a mega city | 2017 | Nigeria | Cars, buses, and Bus Rapid Transit (BRT) | Experimental measurements | The study measured IAQ Measured: CO and VOCs | commuters | NA | NA | The study found average CO levels (4.40–39.78 ppm) were highest in cars, 1.36 times higher than buses, 2.17 times higher than BRT, and 3.67 times higher than pedestrians. VOCs ranged from 0.00 to 0.39 ppm, with vehicle commuters more exposed than pedestrians. |
[48] | Improving cabin comfort with smart auto-flap HVAC control | 2023 | India | Sedan car | Experimental measurements | The study measured Indoor Air Quality parameters: CO2 and PM2.5 | Passengers and Driver | Only AC but varied for IC and EC settings | ASHRAE, WHO and OSHA | The study found that HVAC in IC mode reduced PM levels but raised CO2 (500–4000 ppm), while EC mode lowered CO2 but peaked PM near 350 μg/m3. IC mode with SCL intervention reduced PM to below 60 μg/m3. |
[49] | Noise Exposure Inside a Passenger Car Cabin in Tropical Environmental Condition | 2017 | Malaysia | truck | Experimental measurements | The study measured Noise level: Sound pressure level (SPL) | Diver | NA | ISO 51228 [50] | The study found that SPL ranged from 44 to 49 dB(A) in vehicles. Noise levels were higher on dirt roads (55–75 dB(A)) than on tarmac (55–68 dB(A)), increasing with speed. A smart HVAC flap improved cabin comfort. |
[51] | Challenges in evaluating PM concentration levels, commuting exposure, and mask efficacy in reducing PM exposure in growing, urban communities in a developing country | 2015 | Indonesia | Sedan (car), motorcycle and Minibus (“Pete-Pete”) | Experimental measurements | IAQ Measured: PM2.5 and PM10 | commuters | NV (for the minibuses) and AC (in Cars) | WHO | The study found surgical masks to be the most effective, reducing PM2.5 by 30% and PM10 by 71%. Cars had the lowest PM levels, and minibuses and motorcycles had the highest. Younger children were most vulnerable to PM exposure, with males having higher inhalation rates. |
[1] | Indoor Environmental Quality Assessment of Train Cabins and Passenger Waiting Areas: A Case Study of Nigeria | 2024 | Nigeria | Trains | Experimental measurements | IAQ, TC, AC, VC, Measured: CO2, RH, To, SPL, PM, VOCs, NO2 and Illuminance, air changes per hour (ACH) | Passenger | AC (closed cabin and curtains) | EN16798-1 [52], EN13272 [53], ASHRAE, OSHA, WHO, NESREA. | The findings indicate that indoor climate, noise, and illuminance were deficient in 9 of the 15 trains surveyed. All Indoor Environmental Quality (IEQ) parameters revealed significant gaps, with inadequate ventilation. PM levels exceeded the referenced limits, suggesting insufficient filtration and ACH in the trains. |
[54] | Assessment of Thermal Comfort in a Car Cabin Under Sun Radiation Exposure | 2018 | Malaysia | Sedan car | EM | The study measured TC parameters: Solar irradiance, Ta, RH | NA | WC, partially Open windows by 20 mm (about 0.79 in), varied shading conditions | DOSH, Malaysia and IAE, Singapore | The study found higher interior temperatures in unshaded parking, with M2 reaching 57.1 °C. Shaded parking had the highest relative humidity (57.7%), while M2 had the lowest at 22%. |
[55] | Mite and cat allergen exposure in Brazilian public transport vehicles | 2004 | Brazil | Buses (public buses) and sedans (taxis) | EM | The study measured IAQ parameters such as dust and Indoor allergens like Dermatophilosis | Passenger and driver | NV and AC ventilation | NA | The study found high mite allergens across all vehicles. AVBs had higher Der p 1 (4.3 μg/g) and Der f 1 (2.4 μg/g) than NVBs. Fel d 1 levels (1.5–1.6 μg/g) were consistent across buses, while taxis posed allergenic risks, making public transport allergen reservoirs contributing to indoor contamination. |
[56] | Passengers’ Thermal Comfort in Private Car Cabin in Hot Climate | 2018 | Egypt | Sedan (simulated) | Computational fluid dynamics | TC and HVAC systems Measured: Ta, solar irradiation, PMV, PPD, AV | NA | AC | ASHRAE 55 [57] and ISO 7730 [58] | Using CFD the study investigated airflow patterns and TC with the effect of solar emission in car cabins. PPD and PMV are decreased with an increase in discharge angles. Also, PMV and PPD parameters were used to evaluate the discharge Va, and angle effects in-cabin. They concluded that a bigger air flow rate at the same Ta enhances TC, and discharge orientation affects TC |
[58,59] | Development of novel control strategy for multiple circuit, roof top bus air conditioning system in hot humid countries | 2008 | Malaysia | Bus (simulated bus) | EM | TC, HVAC control systems, and Energy saving/cost. RH, Ta, Pressure, and Air flow rate. | NA | AC (Varied settings) | ASHRAE | The study developed an automatic controller for a multiple-circuit AC system in Malaysian buses, achieving 31.6–51.4% energy savings, $656 annual cost savings, and PMV (0.66–0.07) with PPD (15.3–5.1%), maintaining thermal comfort better than conventional systems. |
[19] | Assessment of thermal comfort parameters in various car models and mitigation strategies for extreme heat-health risks in the tropical climate | 2020 | India | Sedan, SUV, and Hatchback | EM | IAQ and TC Measured: CO2, RH, Ta, CO, mean radiant, Tr PMV and PPD | Virtual occupant | AC and WC | ASHRAE 55, EN 15251 [60] ISHRAE [61] | The study found CO, Ta, and Tr exceeded comfort limits in all vehicle models. PMV values (SUVs: 8.36–16.75, hatchbacks: 8.54–17.38) were inadequate per ASHRAE standard but met ISHRAE standards, highlighting thermal discomfort. |
[25] | Aerosol influenza transmission risk contours: A study of humid tropics versus winter temperate zone | 2010 | Costa Rica, El Salvador, Nicaragua, Panama, Peru, Thailand, Singapore, New Guinea, Australia. | Sedans, buses, aircraft, and buildings | EM | IAQ, Measured: T and RH. | Passengers and patrons | AC, WC, and WO | NA | The study assessed contagion risks in tropical buildings and transport modes. Old taxis and new cars had low risks due to efficient HVAC systems. Luxury buses posed higher risks from in-cabin aerosols, while aircraft had the lowest risk due to short exposure times and effective ventilation. |
[62] | Enhancement of Thermal Comfort Inside the Kitchen of Non-Air-conditioned Railway Pantry Car | 2020 | India | Train (kitchen Pantry cars) | EM and NS via CFD | TC, ventilation and energy efficiency Measured: Ta, globe temperature (Tg), Va, RH | Chefs | NAC, Exhaust Fans, Carriage fans and Air-vent | ASHRAE | The study developed a Standard Effective Temperature (SET index (28.6–30 °C) for train pantry kitchens using CFD. An improved design with optimized ventilation and air temperature significantly enhanced thermal comfort during cooking. |
[29] | Indoor thermal management of a public transport with phase change material (PCM) | 2023 | Bangladesh | three-wheeler | EM and NS | Thermal comfort Measured: Ta | passengers | NAC, | NA | The study evaluated PCM (sodium sulfate decahydrate) in three-wheelers, achieving temperature reductions of 3.8 °C (single layer) and 7.5 °C (double layer). PCM reduced interior temperatures by 4 °C but was ineffective with occupants or engines running, suggesting additional PCM layers near engines for better control. |
[63] | Thin Ceiling Circulator to Enhance Thermal Comfort and Cabin Space | 2019 | Japan | Sedan (compact 3-row seaters) | EM and NS via CFD | TC and ventilation parameters Ta, RH, radiation, and Va solar radiation, vehicle speed. | Thermal manikins | AC and circulator and air blower | NA | The study evaluated a new circulator, improving rear-seat thermal comfort by enhancing air distribution. CFD and experiments showed increased AV (+0.3 m/s), reduced temperature (−1.4 °C), improved thermal sensation (~1.5 points), and 30% height reduction for more cabin space. |
[31] | In-Situ Studies on the Effect of Solar Control Glazings on In-Cabin Thermal Environment in Hot and Humid Climatic Zones | 2020 | India | Two sedan model vehicles | EM | Thermal comfort Measured: Va, RH, Ta, Tg, solar irradiance. | NA | NA | ISO 7726 [64] and ISO 14505 [65] | The study evaluated solar thermal load control via glazing, finding reductions in Ta (2–4 °C), Teq (4–8 °C), cooling time (5–7 min), and heating time (11–16 min). Absorbent glazing was more cost-effective, lowering Ta, Tr, and Teq effectively. |
[30] | Environmental conditions driven method for automobile cabin pre-conditioning with multi-satisfaction objectives | 2022 | Saudi Arabia. | sport utility vehicle (SUV) | EM and MLA | IAQ, TC, and Energy consumption solar radiation intensity, RH, and atmospheric temperature. | NA | AC | NA | The study developed a comprehensive evaluation index (CEI) to assess thermal environments, achieving 92.3% accuracy with a Cubic SVM algorithm. Tcabin was highest during decreasing solar radiation. The CEI integrated PMV, temperature, air quality, and energy efficiency for passenger satisfaction evaluation. |
[32] | Improvement of AC System for Bus with Tropical/Hot Ambient Application | 2023 | Kuwait, KSA, Qatar and UAE | Bus | EM and NS via CFD | TC and AC efficiency Measured: irradiance, in cabin Ta and Va | Thermal manikins | AC (recirculation mode) | NA | The study’s three DOE experiments improved heat load reduction (3%) and airflow (1.2 m/s). DOE1 optimized duct layouts, boosting air discharge by 20%. DOE2 enhanced airflow control (1–10%) with a blower and BLDC motors. DOE3 added insulation and solar green glass. |
[66] | Improvements in energy saving and thermal comfort for electric vehicles in summer through coupled electrochromic and radiative cooling smart windows | 2024 | China | EV—Sedan | EM, NS and MM | TC and energy savings Measured: Ta, RH, solar radiation (surface, direct, and diffused) | NA | AC | ASHRAE-55, GB7258 [67] | The study found SET* higher for front passengers and near windows. Electrochromic coloration targeted 26 °C SET*, saving 762 W. Radiative cooling lowered TWS by 10.7 °C and SET* by ~7 °C. Scattered solar radiation significantly increased cooling loads. |
[68] | Impact of Different Types of Glazing on Thermal Comfort of Vehicle Occupants | 2020 | India | Hatchback -sedan | EM | Thermal comfort Measured: Ta, Solar radiation, RH | 4 passengers | AC (recirculation) | IS 2553 [69] | The study evaluated spectral transmissivity and heat transmittance of various vehicle glazing options. The dark grey glass showed the highest IR and UV blocking, followed by dark green and green. For Tropical India, recommended configurations included green glass for back doors, WS IR cut for windscreens, and dark green for windows. |
[70] | Numerical Evaluation of Vehicle Orientation and Glazing Material Impact on Cabin Climate and Occupant Thermal Comfort | 2017 | India | Sports Utility vehicle (SUV) model | NS (1D/3D CFD) | TC Measured: Ta, irradiance Including transmissivity, absorptivity, conductivity, density | NA | AC | ASHRAE | The study evaluated six vehicle heat load cases, finding thermal sensation ranged from slightly warm (0.37) to slightly cool (−0.58), improving with IRR glazing and closed blinds. North-facing vehicles had higher solar heat loads than east-facing, with AC pull-down cycles simulated at 50, 100, and 0 km/h. |
[42] | Potential health risks due to in-car aerosol exposure across ten global cities | 2021 | Bangladesh, India, China, Brazil, Egypt, Columbia, Iraq, Ethiopia, Malawi and Tanzania | Sedan | EM | IAQ and PE Measured: PM2.5 (PM ≤ 2.5 μm) | NA | WO, WC+ Fan and WC+ AC-IC mode | WHO | The study evaluated the relationship of exposure to PM2.5 in 10 global cities, highlighting hotspots like Dar-es-Salaam (81.6 μg/m3), Blantyre (82.9 μg/m3), and Dhaka (62.3 μg/m3), with significant health burdens. It found correlations between pollution, socioeconomic disparity, and economic losses in low-GDP cities. |
[71] | Experimental Study on the Improvement of Thermal Comfort Inside a Car Cabin | 2023 | Malaysia | sedan | EM | Thermal comfort Measured: Ta in cabin, Va | NA | Cooling fans, WO, | NA | The study found cooling fans reduced in-cabin Tcabin by 4.8 °C in S1 (WC + Fan), but temperatures rose quickly. S2 (WO + fan + green blankets) achieved a stable 3 °C drop, while S3 (shaded windscreen + fans) showed a stable Ta reduction, maintaining effectiveness. |
[72] | A pilot study on thermal comfort in Indian Railway pantry car chefs | 2019 | India | Railway pantry car | EM and SM | Thermal comfort Measured: Ta, Tr, Tg, Va, RH | chefs | NAC and AC | ASHARE 55 and BEE, India | The study found higher thermal discomfort in non-AC rail pantry cars (PMV: 2.93, PPD: 99%) versus AC cars (PMV: 2.17, PPD: 84%). Cooking temperatures exceeded ASHRAE limits, with 86% of chefs reporting discomfort and warm sensations. |
[73] | Study on Human Comfort of Military Vehicles in Malaysian Tropical Environment | 2023 | Malaysia | Military vehicles (logistic, utility, and armored) | EM | Human comfort; noise, vibration, and heat stress | NA | NA | ISO 5128 DOSH, [50] | The study assessed military vehicles for noise (76.4–84.3 dB(A)), WBV (0.4–0.9 m/s2), and heat stress, highest in logistics vehicles. All were within comfort limits, with utility vehicles rated most comfortable. |
[74] | Improving microbial air quality in air-conditioned mass transport buses by opening the bus exhaust ventilation fans | 2005 | Thailand | Buses | EM | IAQ Measured: bacterial and fungal counts | Passengers and drivers | AC, Opened exhaust ventilation fans (OEVF) | WHO | The study found bacterial and fungal counts significantly lower in buses with OEVF (83.8 ± 70.7, 38.0 ± 42.8 cfu/m3) than without (199.0 ± 138.8, 294.1 ± 178.7 cfu/m3). Among 39 AC buses, 17 met acceptable microbial levels (<500 cfu/m3), while 4.6% exceeded limits. |
[18] | Variation of PM2.5 and inhalation dose across transport microenvironments in Delhi | 2024 | India | Bicycle, sedan, hatchback, auto-rickshaws, MTW, buses, metro. | EM | IAQ Measured: PM1-PM10, RH, Ta, Pressure, Wind Speed, Direction. | Passengers and drivers | AC and NAC, NV, | NA | The study found PM2.5 highest in bicycles (59.8 μg/m3) and metro 55.7 μg/m3, lowest in AC cars (40.1 μg/m3). Exposure: Bicycle Metro MTW non-AC modes, Cycling had the highest inhalation doses, worsened during peak hours and hotspots. |
[75] | Improving Thermal Comfort and Ventilation in Commercial Buses in Nigeria in COVID-19 Era | 2022 | Nigeria | Minibus and big bus | EM | Thermal Comfort Measured: Ta, RH, Va | Passengers and drivers | NV, WO, door (opened) | ASHRAE 55 | The study found peak in-cabin temperatures of 40 °C due to open windows, with heat load decreasing as air inflow increases with bus speed. Overcrowding (60–80 passengers) contributed to higher heat. |
[76] | Evaluating the influence of ambient conditions in the cooking space of railway pantry car using selected thermal indices and physiological parameter | 2024 | India | Railway pantry car (RPC) | EM | Heat stress index Measured: | chefs | NA | The study found mean heat stress indices: UTCI (37.77 °C), WBGT (30.42 °C), DI (30.05 °C), TSI (33.21 °C), and HI (48.53 °C), indicating inadequate thermal conditions for chefs in RPC environments. | |
[43] | In-car particulate matter exposure across ten global cities | 2020 | Bangladesh, India, China, Brazil, Egypt, Columbia, Iraq, Ethiopia, Malawi and Tanzania | Sedan | EM | IAQ and PE Measured: PM ≤ 2.5 μm (PM2.5) and ≤10 μm (PM2.5–10) | Driver and passengers | FAN, WO and WC (fan-on and recirculation) | WHO | The study found PM2.5 exposures lower during off-peak hours, with WO settings showing the highest PM2.5 and PM10 levels. Fan-on and recirculation modes reduced exposure, highlighting the influence of hotspots, journey time, and in-car PM on inhaled doses. |
[77] | Effect of ambient concentration of Carbon monoxide (CO) on the in-vehicle concentration of Carbon monoxide in Chennai, India | 2020 | India | Sedan and bus | EM | IAQ and PE Measured: Carbon monoxide (CO) | commuters | AC + REC, AC-FA, and WO | NAAQS, India. | The study found in-vehicle CO levels (mg/m3) lowest in AC-IC (2.4) and highest in WO (5.7). AC + REC minimized CO ingress, which is ideal for short trips, while AC + EC or WO is suitable for long journeys. |
[78] | Exposure to fine particulate, black carbon, and particle number concentration in transportation microenvironments | 2017 | Colombia | Walking, cycling bus, car, taxi, motorcycle and Bus Rapid Transit (BRT) | EM | IAQ and PE Measured: PM2.5, black carbon, and number of sub-micron particles | commuters | AC + REC, WO, NV | NA | The study revealed the highest PM2.5 and eBC levels in diesel-powered BRT buses. Pedestrians experienced three times higher doses in street canyons, while BRT buses had the highest pollution exposure. |
[79] | Personal Exposure to PM2.5 in the Massive Transport System of Bogotá and Medellín, Colombia | 2020 | Colombia | BRT (diesel), metro (electric), cable metro, metro plus (CNG trams). | EM | IAQ and PE Measured: PM2.5 | commuters | AC, WC and WO (90% WO) | WHO | The study found that mean PM2.5 levels and personal dose in diesel-powered TM vehicles were 167 μg/m3 and 2.3 μg/min, respectively, compared to 41 μg/m3 and 0.53 μg/min in SITVA (electric/CNG). TM users faced four times higher doses than SITVA, while tramcars had the lowest exposure. |
[80] | Variations in individuals’ exposure to black carbon particles during their daily activities: a screening study in Brazil | 2018 | Brazil | Sedan, bus, walking | EM | IAQ and PE Measured: BC | 12 volunteers | WO and WC | NA | The study found transport modes contributed 7% to total exposure, with highest BC levels in buses (5.80 μg/m3) and walking (5.34 μg/m3). Transport accounted for 17% of exposure. |
[81] | Commuter exposure to black carbon particles on diesel buses, bicycles and on foot: A case study in a Brazilian city | 2017 | Brazil | bus, walking and bicycle | EM | IAQ and PE Measured: BC | Commuters | WO and WC | NA | The study found mean BC levels of 9.6 μg/m3 (buses) and 5.1 μg/m3 (walking/bicycling), with bus peaks at 60.0 μg/m3. Cyclists (2.6 μg) and pedestrians (3.5 μg) had higher inhalation doses over 1.5 km than bus commuters. |
[82] | Commuter exposure to particulate matters in four common transportation modes in Nanjing | 2019 | China | Subway cabins and stations, bicycles, buses, and walking | EM | IAQ and PE Measured: CO2, PM1 and PM2.5 | Commuters | HVAC | NA | The study found subway cabins had the lowest PM levels (PM1: 38.3 μg/m3, PM2.5: 54.4 μg/m3), while bus cabins had higher levels (PM1: 56.0 μg/m3, PM2.5: 74.4 μg/m3). Pedestrians had the highest PM1, with no seasonal impact on PM levels. |
[83] | Exposures to multiple air pollutants while commuting: Evidence from Zhengzhou, China | 2020 | China | bike, taxi, subway and bus | EM | IAQ and Personal exposure. Measured: PM2.5, PM10, SO2, CO, O3 and NO2, Ta, RH | Commuters | WC, AC and NAC | NA | The study found PM2.5 inhalation doses (mg): taxi (3120), bus (12,636), bike (32,643), subway (19,500). PM2.5 and PM10 levels peaked in bikes and subways, with taxis and buses showing higher mean PM, O3, SO2, and CO levels. |
[84] | Bus commuter exposure and the impact of switching from diesel to biodiesel for routes of complex urban geometry | 2020 | Brazil | BRT buses | EM | IAQ and PE Measured: PM2.5 | Commuters | WC settings | NA | The study found that mean in-cabin PM2.5 levels in diesel buses were 20.1 ± 20.0 μg/m3, while for biodiesel buses they were 3.9 ± 26.0 μg/m3. The Particle Number Concentration (PNC) was lower in diesel buses (43.3/cm3) compared to biodiesel buses (56.6/cm3). |
[85] | Car users exposure to particulate matter and gaseous air pollutants in megacity Cairo | 2020 | Egypt | Sedan car | EM | IAQ and PE Measured: PM2.5, PM10 NO2, CO | Commuters | WC, WO, AC and | NA | The study found PM10 (227 μg/m3) and PM2.5 (119 μg/m3) highest with windows open, exceeding AC mode. PM2.5 peaked in evening rush hours, showing coarser in-cabin particles. |
[86] | Commuter exposure concentrations and inhalation doses in traffic and residential routes of Vellore city, India | 2020 | India | Bicycle, walking, motorbike, car, auto-rickshaw (AR), and bus | EM | IAQ and PE Measured: PM1, PM2.5, wind speed, RH and Ta | Commuters | WO | NA | The study found higher PM2.5 levels on traffic routes, with morning levels (212 μg/m3) exceeding afternoon (124 μg/m3) for buses. Motorbikes had the highest PM1 exposure (172 μg/m3), while active commuting modes had four to eight times higher inhaled doses than passive modes. |
[87] | PM2.5 exposure in highly polluted cities: A case study from New Delhi, India | 2017 | India | auto-rickshaw (AR), cars and bus | EM | IAQ and PE Measured: PM2.5 and BC | Commuters | WC, WO | NA | The study found PM2.5 and BC levels (μg/m3) were higher in winter 489.2 than summer 53.9. Transport contributed most to BC, while cooking and cleaning increased PM2.5. |
[88] | Environmental justice in the context of commuters’ exposure to CO and PM10 in Bangalore, India | 2014 | India | car, two-wheeler, bus, company vehicle and walk | EM and SM | IAQ and PE Measured: PM10, CO and RH | Commuters | WO, NAC, AC | NA | The study found two-wheelers had the highest PM10 375 μg/m3 and CO 5.4 ppm levels, followed by cabs. In-cabin pollutants stemmed from vehicular emissions and background PM10. |
[89] | Probabilistic health risk of volatile organic compounds (VOCs): Comparison among different commuting modes in Guangzhou, China | 2018 | China | car, airbus, subway, and bicycle | EM | IAQ and PE Measured: VOCs | Commuters | AC, NAC | USEPA | The study found that the risk probability for bus, car, bicycle, non-AC bus, and subway exposure to pollutants greater than 10−6 was approximately 90% and 92%, respectively. Formaldehyde, benzene, and acrolein had the highest risk. |
[90] | Health risk assessment and personal exposure to volatile organic compounds (VOCs) in metro carriages—A case study in Shanghai, China | 2016 | China | Metro carriages (trains) | EM | IAQ and PE Measured: VOCs (benzene, toluene, ethylbenzene, xylene) | Commuters | AC, NAC | WHO | The study found higher VOC levels in old metro carriages. Underground acetone and acrolein exceeded above-ground by 10%, rising with commuter density, reaching 26.2 μg/m3. |
[91] | Investigation of volatile organic compounds exposure inside vehicle cabins in China | 2015 | China | Sedan cars | EM | IAQ and PE Measured: CO2, TVOC, CO and H2S | Commuters | No-fan + no-RC, fan + no-RC and fan +RC | NA | The study reported mean VOC levels (μg/m3): benzene (16.73), toluene (66.0), xylene (14.2), ethylbenzene 6.7, styrene (28.09), formaldehyde 16.4, acetaldehyde 12.4, acetone 20.6. VOCs were higher in new vehicles and leather interiors. |
[92] | The commuters’ exposure to volatile chemicals and carcinogenic risk in Mexico City | 2005 | Mexico | Private car, microbus, bus, and metro | EM | IAQ and PE Measured: VOCs | Commuters | WO (microbus), WC (bus, car) | NIOSH, TO-11A | The study found lifetime carcinogenic risks highest in microbuses (3.1 × 10−5–4.0 × 10−5) and lowest in metros (1.3 × 10−5–1.7 × 10−5). VOC exposure was highest in cars. |
[93] | Commuters’ exposure to PM2.5, CO, and benzene in public transport in the metropolitan area of Mexico City | 2004 | Mexico | Minibus, bus, metro | EM | IAQ and PE Measured: PM2.5, CO, and benzene | commuters | NA | USEPA | The study found that PM2.5 was mostly carbon (50%), with in-cabin levels ranging from 12 to 137 μg/m3. The highest levels were observed on buses during evening trips (137 μg/m3), followed by minibusses and metros. |
[94] | Carbon monoxide levels in popular passenger commuting modes traversing major commuting routes in Hong Kong | 2001 | Hong Kong | bus, minibus and taxi | EM | IAQ and PE Measured: CO | Commuters | AC (buses) NAC (buses) | NA | The study found mean in-cabin CO levels of 1.8 ppm (bus), 2.9 ppm (minibus), and 3.3 ppm (taxi), influenced by breathing height. CO levels peaked on urban–suburban routes, with no significant differences between AC and non-AC buses. |
[95] | Analysis of various transport modes to evaluate personal exposure to PM2.5 pollution in Delhi | 2021 | India | rickshaw, bus, metro, car and walking | EM | IAQ and PE Measured: PM2.5 | Commuters | AC | NAAQS | The study found the highest PM2.5 levels in rickshaws (266 ± 159 μg/m3) and the lowest in metros (72 ± 11 μg/m3). AC cars exceeded the 24-h NAAQS. Walking had the highest respiratory deposit dose, and rickshaws and non-AC cars. |
[96] | Exposure to traffic-related particulate matter and deposition dose to auto rickshaw driver in Dhanbad, India | 2019 | India | auto rickshaw | EMand SM | IAQ and PE Measured: PM10, PM2.5 and PM1 | Drivers | NA | NA | The study found in-cabin PM levels were 3.3 times higher than ambient, with PM10 at 844 μg/m3 the highest. PM1 had the highest levels, causing body pain, eye irritation, and headaches in drivers. |
[97] | On-road PM2.5 pollution exposure in multiple transport microenvironments in Delhi | 2015 | India | Bicycle, auto-rickshaw, two-wheeler car, bus, metro | EM | IAQ and PE Measured: PM2.5 | Commuters | AC and WO (car and bus) | NA | The study found on-road PM2.5 levels exceeded ambient levels by 10–40%, with cycling exposure nine times higher than AC cars. Ambient PM2.5 ranged from 130 to 250 μg/m3, highlighting significant exposure risks across modes. |
[98] | A comparison of personal exposure to air pollutants in different travel modes on national highways in India | 2017 | India | Car (AC and non-AC) and bus | EM | IAQ and PE Measured: PM2.5, CO, and CO2 | commuters | AC + REC +WC and NAC+ WO | WHO | The study found that the mean PE for PM2.5 (μg/m3) was highest in cars (85.41 ± 61.85), followed by buses (75.08 ± 55.39), and AC cars (54.43 ± 34.09). CO exposures were highest in AC cars, while PM2.5 was lowest in these vehicles. |
[99] | Effect of modes of transportation on commuters’ exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in Chennai, India | 2019 | India | Bus, car, and motorbike | EM and SM | IAQ and PE Measured: PM2.5 and NO2 | Commuter | AC + WC (cars) | NA | The study found mean PM2.5 levels were highest for motorbikes (251 μg/m3), followed by cars (224 μg/m3) and buses (225 μg/m3). Motorbikes also had the highest PM2.5 exposure rate (2.00 μg/m3/min) and NO2 exposure (1.04 μg/m3/min). |
[100] | Commuter exposure to Air Pollution in Newcastle, U.K., and Mumbai, India | 2014 | U.K and India | Bus, car, bicycle, and train, | EM | IAQ and PE Measured: PM10 and CO | Commuter | AC (taxi), non-AC (car) | NA | They found that Mumbai buses had the highest PM10 levels, 502.7 μg/m3, and NAC cars had the highest CO levels, 6.4 mg/m3, making overall pollution exposure higher than in Newcastle. |
[101] | Traffic-related occupational exposures to PM2.5, CO, and VOCs in Trujillo, Peru | 2005 | Peru | Car (taxi) bus and Van | EM and SM | IAQ and occupational exposure: PM2.5, CO, and VOC: benzene/toluene | Driver and workers | NA | NIOSH, OSHA, ACGIH | They found bus commuters had the highest PM2.5 exposures (161 ± 8.9 μg/m3), followed by gas station attendants (64 ± 26.5) and office workers (65 ± 8.5). BTEX levels exceeded safe thresholds, with smokers at higher risk. |
[102] | Coconut oil as phase change material to maintain thermal comfort in passenger vehicles | 2018 | Saudi Arabia | Sedan | EM | Thermal comfort Measured: Temperature | NA | NA | NA | Coconut oil as PCM can potentially lower Tcabin to ~15 °C enhancing in-cabin thermal climate depending on time, duration, and parking location. |
[103] | Human Health Implications of Vehicular Indoor Air Pollution for Commuters in Selected Road Routes in Port Harcourt Metropolis | 2024 | Nigeria | Bus | SM | Surveyed IAQ and Noise and health risks | Drivers | NA | NA | The study found that 42.7% of respondents were exposed to in-vehicle pollutants for 1–5 h daily, 46.8% for 6–10 h, and 10.5% for over 10 h. Health impacts included cough, shortness of breath, respiratory infections, stress disorders, heart ailments, and pneumonia. |
[104] | Indoor Environmental Quality: Sampling in One of the Sao Carlos’ Public Buses | 2016 | Brazil | Buses | EM | IEQ Measured: Ta, RH, noise, CO, CO2, PM2.5 and PM10 | Driver and passengers | NV via WO | NR:15 [105], NHO, CONAM, ANVISA and WHO | The study reported air temperature (17–38 °C), relative humidity (19–87%), and heat index (69–104 °F). CO2 ranged from 491 to 1959 ppm (mean: 920 ppm), and PM2.5 levels were 24–48 μg/m3, deeming bus environments unhealthy for drivers and collectors due to pollutants. |
[106] | Personal exposures to particulate matter in various modes of transport in Lagos city, Nigeria | 2016 | Nigeria | cars, buses, Bus Rapid Transit (BRT), and walking | EM | IAQ and PE Measured: PM10 and PM2.5 | Driver and passengers | WO and NAC | NA | The study found mean PM10 and PM2.5 levels (μg/m3) highest in pedestrians (476.35 and 206.83) and exceeded WHO limits, with rush hour levels (PM10: 413.4, PM2.5: 167.35) posing significant commuter health risks. |
[107] | Air pollutant concentrations and comfort index in commercial buses within Abeokuta Metropolis, South-Western Nigeria | 2024 | Nigeria | buses | EM | TC, IAQ and PE Measured: Ta RH, CO, PM2.5 and PM10. | Driver and passengers | WO and NAC | WHO and USEPA | The study found mean thermal parameters: Ta (35.6–36.0 °C) and RH (57.9–62.4%). Air pollutants exceeded WHO IAQ limits: CO (29.8–32.7 mg/m3), PM2.5 (25.3–44.2 μg/m3), and PM10 (108.3–117.4 μg/m3). |
[108] | Study of Noise, Vibration and Harshness (NVH) for Malaysian Army (MA) 3-Tonne Trucks | 2014 | Malaysia | Military truck (3-tonne) | EM | Comfort: Noise Vibration and Harshness (NVH) | NA | Driver | The study found maximum vehicle speed at 60 km/h. Sound pressure levels were 65.5 dB(A) in idle mode and 73 dB(A) while moving. Vibration levels peaked at 4.28 m/s2 on the steering wheel during motion. | |
[109] | Noise, Vibration and Harshness (NVH) Study on Malaysian Armed Forces (MAF) Tactical Vehicle | 2012 | Malaysia | 4 × 4 Troop Transporter vehicle | EM | Comfort: Noise Vibration and Harshness, whole body vibration and hand-arm vibration. | NA | Driver and passengers | OSHA | The study found tolerable sound pressure levels (SPL) at 84 dB(A) in the rear and 78 dB(A) in the front cabin at speeds of 0–90 km/h. Hand-arm vibration (HAV) remained below 1.5 m/s2, but whole-body vibration (WBV) exceeded 1.15 m/s2 for passenger 1 at 90 km/h. |
[110] | Exposure to ultrafine particles and PM2.5 in four Sydney transport modes | 2010 | Australia | Train (electric), bus(diesel), ferry and automobile | EM | IAQ and PE Measured: UFP, PM1 PM2.5 | Commuters | NV (ferry) and AC (car, trains and buses) | NA | The study found the highest UFP (8.4 × 10⁴ particles/cm3) and PM2.5 (29.6 μg/m3) in buses, with ferries exposing occupants to 3.7 times more PM2.5. |
[111] | Commuter exposure to particulate matter for different transportation modes in Xi’an, China | 2017 | China | Car, subway (trains and station, bus, walking | EM | IAQ and PE Measured: PM10, PM2.5, PM1 | Commuters | WC + AC, WC + AC +REC | NA | The study found lowest PM exposure in cars with WC + AC + REC (PM10: 11.83 μg/m3, PM2.5: 10.09 μg/m3), and highest while walking (PM10: 127.23 μg/m3, PM2.5: 71.59 μg/m3). PM exposure varied by mode and ventilation. |
[112] | Particle exposure and inhaled dose during commuting in Singapore | 2017 | Singapore | Walking, subway bus, taxi | EM | IAQ and PE Measured: PM2.5, UFP, BC, PAHs, PN, CO, RH, Ta | Commuter | WC + AC (used in MRT, Bus, car), | NA | The study ranked exposure levels as walking > subway > buses > taxis. Sidewalks had the highest PM2.5 (36 μg/m3), PN (44,038 cm−3), and BC (6.7 μg/m3). Pedestrians inhaled 2.6–3.2 times more PM2.5 and UFP than subway commuters. |
[113] | Daily personal exposure to black carbon: A pilot study | 2016 | Australia | Bus, train, sedan car, cycling and residential building, | EM | IAQ and PE Measured: BC | A person | WO, WC, FAN, AC + REC, | NA | The study found that the arithmetic mean 24-h BC exposure was 603 ± 1550 μg/m3, with a geometric mean of 306 ± 3.7 μg/m3. BC levels were highest in cars and non-AC buses, highlighting ventilation effectiveness in reducing in-cabin BC. |
[114] | Black Carbon Personal Exposure during Commuting in the Metropolis of Karachi | 2022 | Pakistan | Motorbikes, auto-rickshaws (AR), cars, and buses | EM | IAQ and PE Measured: BC | Commuter | WO + FAN, NAC | USEPA | The study found that motorbikes had the highest BC exposure (26.9 μg/m3 peak-time), buses the lowest, and auto-rickshaws the highest inhalation doses, with commuting significantly contributing to daily BC exposure despite 87.6% time indoors. |
[115] | Personal exposure to black carbon during commuting in peak and off-peak hours in Shanghai | 2015 | China | taxi, bus, subway, cycling and walking | EM | IAQ and PE Measured: BC | Commuters | WC + AC-REC (bus, taxi), WO+ NAC (taxi), AC (trains). | NA | The study found the highest mean BC exposure in subways (9.43 ± 2.89 μg/m3) and lowest while walking (5.59 ± 1.02 μg/m3). Inhalation doses and PE levels followed the same pattern: taxi < subway < cycling < bus < walking. |
[116] | Heterogeneity of passenger exposure to air pollutants in public transport microenvironment. | 2015 | Hong Kong | Bus, trains, subway, termini, platforms, MTR. | EM | IAQ and personal exposure Measured: BC, CO, PM2.5 and UFP | Commuters | NA | NA | The study found higher mean PM2.5 and BC levels in buses than in MTR. Diesel buses had the highest BC and UFP levels. PE doses for PM2.5, BC, UFP, and CO was higher in buses. |
[117] | Exposure level of carbon monoxide and respirable suspended particulate in public transportation modes while commuting in urban area of Guangzhou, China | 2002 | China | Bus, subway trains, and taxi | EM | IAQ and personal exposure Measured: CO, CO2 PM10, PM2.5 | Commuters | WC + AC and NAC (bus and taxi) | USEPA | The study found mean CO levels of 3.1 ppm in the subway. PM10 and PM2.5 levels were highest in non-AC buses (203 μg/m3, 145 μg/m3) and lowest in the subway (67 μg/m3, 44 μg/m3). The PM2.5/PM10 ratio was 76–83%. |
[118] | Influences of commuting mode, air conditioning mode and meteorological parameters on fine particle (PM2.5) exposure levels in traffic microenvironments. | 2012 | China | bus, taxi (AC and non-AC) and metro, walking, bicycle, and motorcycle | EM | IAQ and personal exposure Measured: PM2.5, Ta, RH, Wind speed | commuter | WC + AC and WO + NAC | NA | The study found that mean PM2.5 levels (μg/m3) were highest for buses (75.9) and motorcycles (77.1), followed by bicycles (76.8), walking (74.1), taxis (56.8), and metro (27.9). On-road commutes had higher PM2.5 levels, reaching up to 76 μg/m3. |
[119] | Comparisons of commuter’s exposure to particulate matters while using different transportation modes | 2005 | Taiwan | motorcycle, car, bus and MRT | EM | IAQ and personal exposure Measured: PM10, PM2.5, PM1. | Commuters | AC and NAC | NA | The study found the highest PM levels in buses (PM10: 69.6 μg/m3), with greater idling-driving differences for motorcycles (PM10: 5) than buses (PM10: 3), compared to cars and MRT. |
[120] | Commuter exposure to particulate matter in public transportation modes in Hong Kong | 2002 | Hong Kong | bus, tram, public light bus, taxi, ferry, and Railway (3 types) | EM | IAQ and personal exposure Measured: PM10 | Commuters | AC and NAC | The study found that mean PM10 levels (μg/m3): AC bus (74), non-AC bus (112), subway (44), taxi (58), marine transport (50), railway (145), and road trams (175). The upper deck PM10 levels were lower than the lower deck. AC vehicles and railways were recommended over NAC options. | |
[121] | Carbon monoxide levels measured in major commuting corridors covering different landuse and roadway microenvironments in Hong Kong | 2002 | Hong Kong | Sedan (light good) | EM | IAQ and PE Measured: CO | Commuters | AC and NAC | NA | The study compared in-vehicle to out of vehicle CO levels. The mean in-vehicle CO levels reported was tunnel (8.0 ppm) highway (1.5 ppm) on-road (2.4 ppm) on-road (2.4 ppm) in-vehicle (1.9 ppm). In-vehicle, variations were affected by ambient outdoor affirming the effect of ambient pollution in vehicle ME. Also, they found that the route and time of day affected indoor CO exposure levels. |
[122] | Relationship Between Indoor Air Pollutants Exposure and Respiratory Symptoms Among Bus Drivers in a Malaysian Public University | 2023 | Malaysia | Bus (diesel-fueled) | EM and SM | IAQ and PE Measured: PM2.5, PM10 and NO2 and occupants surveying | Drivers | NA | OSHA, ICOP, Malaysia | The study found bus drivers had higher risks of respiratory symptoms than office workers: cough (OR = 2.5), chronic cough (OR = 2.2), and chronic phlegm (OR = 4.6). PM2.5 and PM10 were identified as key pollutant exposure determinants. |
[123] | Nanoparticles on electric, gas, and diesel buses in mass transit buses of Bogotá Colombia | 2023 | Colombia | Buses (electric, CNG, and diesel), | EM | IAQ and PE Measured: nanoparticles of TRAP | Driver and passengers | NA | NA | The study found that nanoparticle levels in electric buses were 47% and 27% lower compared to diesel and CNG buses, respectively. PM sizes were smaller in BEVs. Mean nanoparticle levels and Lung-Deposited Surface Area were lowest in BEVs. |
[124] | Exposure to particulate matter, CO2, CO, VOCs among bus drivers in Bangkok | 2012 | Thailand | Bus | EM and SM | IAQ and PE. CO, CO2, VOCs, Ta RH, M2.5 | Bus drivers | AC and NAC | WHO, ASHRAE, NAAQS | The study found higher CO2 levels but lower PM2.5 in AC buses, while NAC buses had lower CO2 and higher CO levels, reflecting outdoor air impacts. |
[125] | Exploring the effects of ventilation practices in mitigating in-vehicle exposure to traffic-related air pollutants in China | 2019 | China | Sedan cars (mid-normal sized) | EM | IAQ and PE Measured: CO2, TRAP (PM2.5 and UFP) | Driver and passengers | AC + FA AC + REC, NV + AC + REC | NA | The study found higher mean in-vehicle PM2.5 levels on freeways (119 μg/m3) than on local roadways (93 μg/m3). UFPs averaged 97,227 cm−3 on freeways versus 42,829 cm−3 on local roads, highlighting significant TRAP exposure from polluted ambient air conditions. |
[126] | The threshold effects of bus micro-environmental exposures on passengers’ momentary mood | 2020 | China | Bus | EM and SM | Indoor climate Measured: Noise, PM2.5, Ta, RH, Occupancy survey. | Passengers | AC + FA | WHO, GB 18883 [127] | The study reported averages: noise levels 71.7 dB, PM2.5 23.4 μg/m3, Ta 28.7 °C, RH 45%, passenger load 20, and mood 23.0%. Noise levels exceeded WHO limits, and concerns over environmental conditions in public transport settings. |
[128] | Evaluation of bus driver exposure to nitrogen dioxide levels during working hours | 2019 | Brazil | Bus | EM | IAQ Measured: Nitrogen dioxide (NO2) | Drivers | WO + AC (Hybrid) | ISO/IEC 17025 [129] | The study found higher mean NO2 levels in winter: bus commuters (47.7 ± 16 μg/m3) vs. office workers (23.9 ± 6.5 μg/m3), compared to summer: bus commuters (39.0 ± 12.8 μg/m3) vs. office workers 11.9 ± 6.3 μg/m3 WO ventilation increased NO2 intrusion. |
[130] | Effect of air velocity and relative humidity on passengers’ thermal comfort in naturally ventilated railway coach in hot-dry Indian climate | 2024 | India | Train | EM and SM | Thermal comfort Measured: Va, Ta, RH, Tg | Passengers | AC | ASHRAE | The study found a mean threshold air velocity of 2 m/s, with an acceptable range of 1.1–2 m/s. Only 43% found RH acceptable, and WO settings were common at Ta > 30 °C. |
[131] | Passenger thermal perceptions, thermal comfort requirements, and adaptations in short- and long-haul vehicles | 2009 | Taiwan | Bus and Train | EM and SM | Thermal comfort Measured: Va, Ta, RH, Tg | passengers | WO | ISO 10551 and ISO 14505 [65] | The study found neutral temperatures of 26.2 °C in short-haul and 27.4 °C in long-haul vehicles, with comfort zones of 22.4–28.9 °C and 22.4–30.1 °C, respectively. High temperatures, solar radiation, and low airflow increased thermal discomfort for 2,129 surveyed passengers. |
[132] | Overall and thermal comfort under different temperature, noise, and vibration exposures | 2021 | China | Bus and subway | EM and SM | TC, AC, and sensation. physical and temperature, noise, and vibration. | passengers | FAN, NV | ISO 9886 [133] | The study found noise levels of 70.8 ± 14.4 dB(A) in buses and 73.5 ± 6.1 dB(A) in subways, with vibration levels of 0.66 ± 0.46 m/s2 and 0.18 ± 0.13 m/s2, respectively. Noise and vibration reduced satisfaction and induced warmer sensations. |
[134] | A Comparative Analysis Between Indoor and Outdoor Thermal Comfort Parameters of Railway Pantry Car | 2020 | India | Railway pantry car (RPC) | EM | Thermal comfort Measured: RH, Va, and Ta | Chefs and kitchen staff | (WC, WO, partial- WO) | ASHRAE 55 | The study found indoor parameters: Ta (30.42 °C), Tg (28.68 °C), RH (68.98%), and Va (0.03 m/s). While no significant differences were observed in summer, winter showed variations except for RH and Va. Lunch and snack cooking periods were thermally inadequate. |
[135] | A Field Investigation of the Average Indoor Thermal Comfort Parameters on the Railway Pantry Car Kitchen at the Different Cooking Period | 2021 | India | Railway pantry car (RPC) | EM | Thermal comfort: Measured: RH, Va, Ta, and Tg | Chefs | AC | ASHRAE 55 | The study found TC parameters exceeded ASHRAE 55 limits. Mean indoor values: Ta (30.42 °C), Tg (28.68 °C), RH (68.98%), Va (0.03 m/s). Outdoor values: Ta (25.78 °C), Tg (25.94 °C), RH (66.84%), Va (1.49 m/s). Significant differences existed for Ta, Tg, and Va. |
[136] | Appraisal of Thermal Comfort in Non-Air-conditioned and Air-conditioned Railway Pantry Car Kitchens | 2020 | India | Railway pantry car (RPC) | EM and SM | TC Measured: Va, Ta, and Tr | Chefs | AC | ASHRAE 55 and ISO 7730 and NBC, India | The findings revealed mean Ta values of 29.30 °C for AC and 34.58 °C for non-AC environments, with mean Tr values of 29.57 °C (AC) and 34.05 °C (NAC). Mean RH values were 75% (AC) and 76% (NAC), both exceeding ASHRAE-prescribed limits. |
[137] | Thermal comfort assessment of non-air-conditioned railway coach in Central India during extreme summer | 2023 | India | trains | EM and SM | Thermal comfort: Measured: RH, Va, Ta, and occupants survey. | passengers | NAC | ASHRAE | The study found higher Passenger Comfort Vote for males 1.4 than females (1.3). PCV distribution: fans off (1%), fans on 86%, WO 89%, neutral thermal sensation was at Va = 1.7 m/s, To = 33.2 °C, highlighting ventilation improvements. |
[138] | Thermal comfort of the kitchen in pantry cars on Indian railways | 2019 | India | RPC | EM and SM | Thermal comfort: Measured RH, Va, Ta, Tg, and survey. | chefs | NAC | ASHRAE 55 and ISO 7730 | The study found indoor temperatures of 32 °C (summer) and 29 °C (winter) during cooking, exceeding comfort limits. Thermal neutrality was 23 °C (summer) and 21.62 °C (winter), with comfort ranges of 18.50–27.80 °C and 17.80–25.50 °C, respectively. Improved ventilation was recommended. |
[139] | Characterization and risk assessment of particulate matter and volatile organic compounds in metro carriage in shanghai | 2019 | China | Trains (metro) | EM | IAQ and PE Measured VOCs and PM2.5. | commuters | Central ventilation and AC | WHO, GB 3095 [140] | In this study, VOC levels, PM2.5 concentrations, and LCR of VOCs were higher on the underground tracks than on the above-ground track. PM2.5 and VOCs were 3× higher in old metro carriages, with LCR doubling compared to new ones. |
[141] | Exposure to carbon monoxide, fine particle mass, and ultrafine particle number in Jakarta, Indonesia: Effect of commute mode | 2012 | Indonesia | Car (private) and bus, minibus (public) | EM | IAQ and PE Measured: CO and PM2.5 and UFP particle number (PN) | Commuters | AC (cars, public transport), Non-AC (public transport) | NA | The study measured commuters’ exposure, finding mean car exposures: CO (22 ± 9.4 ppm), PM2.5 (91 ± 38 μg/m3), and particles (290 ± 150 × 103 cm−3). Public transport showed the highest exposure, with CO levels 180–700% higher on-road. |
[142] | Assessment and mitigation of personal exposure to particulate air pollution in cities: an exploratory study | 2021 | Singapore | Walking Bus Taxi/car MRT train | EM | IAQ and personal exposure Measured: CO2 | Staff and student | WC+ PAC, NV (homes), NV+ PAC, AC (MRT, bus, AC+ REC. | NA | The study measured mean exposure levels for different transport modes. Public transport (bus, MRT) and active modes (walking, cycling) showed higher pollutant levels. PM2.5, BC, and UFP were highest in cycling and walking, while CO2 and CO varied across modes. |
[143] | Characterization of PM2.5 exposure concentration in transport microenvironments using portable monitors | 2017 | Hong Kong | minibus, double-decker bus, MTR train | EM | IAQ and personal exposure Measured: PM2.5 | Commuters | NA | NA | The study found higher mean PM2.5 levels in winter (31–47 μg/m3) than in summer (10–23 μg/m3) across transport. In-cabin levels ranged from 31 to 47 μg/m3 (winter) to 12–23 μg/m3 (summer), with outdoor levels similarly elevated in winter. |
[144] | Commuter exposure to inhalable, thoracic and alveolic particles in various transportation modes in Delhi. | 2016 | India | AR, bus, car, motorcycle | EM | IAQ and PE Measured: PM10, PM2.5, PM1 | commuters | WC | NA | The study revealed varying in-vehicle pollutant levels by mode and time, with cars showing the highest PM exposure. Evening commutes posed greater risks across all modes, with PM10, PM2.5, and PM1 levels higher during this period. |
[145] | Commuter exposure to particulate matter in urban public transportation of Xi’an, China | 2020 | China | Subway, bus (CNG and pure electric) and Walking | EM | IAQ and personal exposure Measured: PM10, PM2.5, PM1 | Commuters | WO (CNG bus) AC+ WC (electric bus) | NA | The study showed varying pollutant levels: CNG bus (PM10: 130, PM2.5: 58), pure electric bus (PM10: 24.3, PM2.5: 16.7), subway (PM10: 68, PM2.5: 46.3), and walking (PM10: 149.4, PM2.5: 69.8). Exposure was highest at bus stops and walking. |
[146] | Commuters’ exposure to particulate matter and carbon monoxide in Hanoi, Vietnam | 2008 | Vietnam | Motorbikes, buses, cars, and walking | EM | IAQ and PE Measured: PM10, CO | Commuters | AC (bus and cars) WO (cars) | WHO | The study found mean PM exposure of 455 μg/m3 and CO levels of 15.7 ppm. In-cabin PM10 levels were highest in motorbikes, and AC reduced PM by 62%, but not CO levels. |
[147] | Commuters’ exposure to PM1 by common travel modes in Shanghai | 2012 | China | Diesel buses Gasoline taxi | EM | IAQ and PE Measured: PM1 | Commuters | WC (taxi, buses) | NA | The study revealed highest PM1 concentrations in buses (155 μg/m3), followed by stations, taxis, and trains. Inhalation doses were highest for cycling, walking, and buses, respectively. |
[148] | Effects of commuting mode on air pollution exposure and cardiovascular health among young adults in Taipei, Taiwan. | 2012 | Taiwan | Car, walking, subway (electric), Bus (gas-powered and gasoline), | EM | IAQ and PE Measured: CO, CO2, PM2.5, Temperature, RH, Noise | Commuters | AC and NAC | NA | The study found the highest PM2.5 exposures in walking (42.1 μg/m3), followed by buses and cars. Walking also had the highest noise and TVOCs, with PM2.5 linked to decreased HVR and cardiovascular risks. |
[149] | Estimating the total exposure to air pollutants for different population age groups in Hong Kong. | 2002 | Hong Kong | Subway, Railway, Car/taxi and Bus/minibus, truck/van, Airplane, | EM and SM | IAQ and PE Measured: CO2, PM10, NO2 | commuters | AC (enclosed transit) | NS-Hong Kong | The study found highest PM10 levels in bus/minibus (137.5 μg/m3), NO2 in truck/van and bus/minibus, and CO in bus/minibus (3150 μg/m3), with risks increasing after 2 h of daily commuting. |
[150] | In-cabin exposure levels of carbon monoxide, carbon dioxide and airborne particulate matter in air-conditioned buses of Hong Kong | 2011 | Hong Kong | Bus | EM | IAQ and PE Measure: CO, CO2 and PM10 | Commuter s | AC | NS-Hong Kong | The study found that mean in-bus CO levels (ppm) were highest in Euro IV buses (1510), followed by Euro II (1226) and Euro III (1143). CO2 levels were similar across Euro II, Euro III, and Euro IV (2.2–2.5 ppm), while PM10 levels were highest in Euro III (240 μg/m3). |
[151] | Particulate matter exposures under five different transportation modes during spring festival travel rush in China. | 2021 | China | CRH Trains (short Haul and (long haul) Bus, Car and subway | EM | IAQ and PE Measure: PM2.5, PM10 and PM1 | Commuters | Bus (WC + AC) Car (WC + AC) | WHO | The study found highest PM2.5 levels in cars (166.7 μg/m3) and walking (141.1 μg/m3) during festivals, with post-festival PM reductions across modes. High-speed trains had the lowest exposure risks. |
[152] | Personal exposures to PM during short distance highway travel in India | 2020 | India | Car, bus | EM | IAQ and PE Measured: PM10, PM2.5 and PM1 | commuter | AC bus, Car (NV), AC + FA (car), AC + REC (car) | USEPA, EN 12341 [153] | The study found that AC + REC mode in cars significantly reduced PM levels (PM10: 20, PM2.5: 10, PM1: 7), outperforming buses and other car modes, ideal for short trips. |
[154] | Sequential measurement of intermodal variability in public transportation PM2.5 and CO exposure concentrations | 2016 | Hong Kong | Train, bus (double-deck), Minibus, Train station, Bus stop, Walking, | EM | IAQ and PE Measured: PM2.5 and CO | commuters | NA | The study found mean pollutant exposure levels: PM2.5 in-vehicle (Train: 23 μg/m3, Double-decker bus: 30 μg/m3, Minibus: 27 μg/m3) and at bus stops (40 μg/m3) and train stations (28 μg/m3). CO and CO2 levels were similar across vehicles (23–30 ppm). | |
[3] | The effect of COVID-19 restrictions on particulate matter on different modes of transport in China | 2022 | China | Subway, High-speed train (HST), Bus, Intercity bus (ICB) | EM | IAQ and personal exposure Measured: PM10, PM2.5 and PM1, and BC | Commuter | HVAC + HEPA (airplane, HST), WO (bus), WC/WO(Bus) Car (AC + REC) | WHO | The study found varying mean PM exposure levels across different transport modes: Subway had low PM levels, followed by high-speed trains (HST), buses with higher exposure, and intercity buses (ICB). Airplanes had the lowest levels of PM and BC. |
[155] | Concentrations of fine, ultrafine, and black carbon particles in auto-rickshaws in New Delhi, India | 2011 | India | auto-rickshaw, Car | EM | IAQ and personal exposure Measured: PM2.5, BC | Commuters | WO AC + WC + REC | NA | The study found in-vehicle pollutant levels of PM2.5 (190 μg/m3), BC (42 μg/m3), and PN (280 × 103 cm−3), exceeding ambient concentrations by 1.5, 3.6, and 8.4 times, respectively. |
[156] | In-vehicle carbon dioxide concentration in commuting cars in Bangkok, Thailand | 2016 | Thailand | Sedan | EM | IAQ Measured: CO2, Tcabin, RH | Occupants (2, 3, 4 person) | AC + REC NAC AC + FA | ASHRAE | The study found CO2 levels reached 10,000 ppm in AC + REC mode (0–1885 s). CO2 decreased with AC + FA (3675–4180 s), while NAC and long-term parking caused CO2 levels to increase over time. |
[157] | Exposure levels of particulate matter in long-distance buses in Taiwan | 2009 | Taiwan | Bus | EM | IAQ Measured: PM2.5, PM10, CO2, RH | Passengers and drivers | AC and WO | EPA, USA EPA and WHO | The study found mean pollutant levels PM10 (39.2 μg/m3), PM2.5 (24.4 μg/m3), and CO2 (959 ppm) below Taiwan EPA IAQ guidelines. PM2.5 and PM10 were elevated with window opening, and CO2 increased with passenger numbers. |
[158] | Inequality in personal exposure to air pollution in transport microenvironments for commuters in Bogotá | 2023 | Columbia | Pedestrian, bus, BRT, car, motorcycle, | EM | IAQ, Measure: PM2.5, black BC and (CO) | Commuter | NA | USEPA | The study found a significant disparity in air pollutant doses between the lowest and highest socioeconomic quintiles. Passive modes, especially BRT, had the highest pollutant levels (PM2.5: 164.6 μg/m3, CO: 4305.8 μg/m3). Active modes had lower levels but higher inhalation risks. |
[159] | Indoor Air Quality (IAQ) Onboard A Naval Ship: A Comparative Study Between Compartments | 2023 | Malaysia | Naval ship | EM | IAQ, Measured: RH, CO2, CO, TVOC, and PM10, CH2O, NO2 | Naval crew | NA | ICOP, USEPA, MAAQS | This study analyzed four compartments: wardroom, cabin, MCR, and Bridge. The temperature was highest on the Bridge (26.3 °C) and lowest in the Cabin (22.2 °C). CO2 peaked in the MCR (510 ppm), with TVOC and PM10 also varying significantly across locations. |
[160] | Exposure to Fine Particles Among Bangkok Mass Transit Authority Bus Drivers | 2011 | Thailand | Bus | EM | IAQ, Measured: PM2.5, black CO and CO2 | Bus drivers | AC and NAC | ASHRAE, WHO and NAAQs | The study found that PM2.5 levels exceeded limits, averaging 208.42 μg/m3 in AC buses and 322.01 μg/m3 in non-AC buses. Also, CO2 and CO levels varied significantly between AC and non-AC buses. Mean CO2 was higher in the AC buses. |
[161] | Evaluation of In-Cabin Levels of Fine Particulates and Carbon Monoxide in Shuttle Buses Along a Major Intra-City Route in Benin City, Nigeria | 2016 | Nigeria | Bus | EM | IAQ Measured:PM2.5, CO, Tcabin | commuter | NA | NA | In this study, mean in-cabin pollutants were reported as follows: Diesel Fuel Buses had PM2.5 (85.01 ± 44.79 μg/m3) and CO (4.39 ± 2.14 ppm), while Gasoline Fuel Buses had PM2.5 (115.40 ± 36.98 μg/m3) and CO (9.54 ± 3.63 ppm). |
[162] | In-vehicle air quality in public buses during real-world trips in Kathmandu Valley, Nepal | 2024 | Nepal | Bus | EM | IAQ Measure d: Ta, PM2.5, PM1 and CO2 | commuter | NAC, WO | WHO | The study found in-cabin PM2.5 concentrations of 95.9 ± 40.4 μg/m3, with higher ACH and VPP for diesel buses. Inhalation doses were 5.65 ± 2.32 μg/km for PM2.5 and 4.27 ± 1.79 μg/km for PM1. |
3.2. Overview of Text Occurrence in Titles and Abstracts of SLR Studies
4. Discussion
4.1. RQ2. Overview and Characterization of the IEQ Studies Presented in RQ1
4.1.1. Indoor Air Quality in Tropical PVCs
4.1.2. Thermal Comfort in Tropical PVCs
4.1.3. Acoustic Comfort and Visual Comfort in Tropic PVCs
4.1.4. Ventilation and Energy Efficiency
4.2. RQ3: The IEQ Gaps and Challenges in Tropical PVCs
- ▪
- Elevated risk of ambient pollution reported in several exposure studies in traffic and hotspot areas, which enhance increased in-vehicle pollutant infiltration; a study explored correlation factors between in-car PM2.5 levels, ambient pollution, fuel price, socioeconomic status, and associated health risks in 10 cities. It was determined that both hotspot and free-flow zones contributed to high commuter exposure to PM2.5, with notable implications for health burdens and mortality rates in cities [42]. Six high-activity zones were surveyed and compared to cross-city routes, showing that AC mode lowered in-cabin pollutants except for CO, with ambient PM conditions from zones and construction activities impacting PM levels [85].
- ▪
- Vehicle type and mix (most still use fossil fuels and gas) enhance vehicular emissions and in-cabin risk due to self-pollution. A comparative study of personal PM2.5 exposures in two cities showed that newer vehicles with better ventilation technologies had lower PM levels [79]. A comparative survey of in-cabin BC levels in diesel- vs. biodiesel-fueled buses suggested that biodiesel, coupled with after-treatments and route changes, could reduce emissions risk. Street geometry and ambient BC ingress were also significant factors [84].
- ▪
- Road infrastructure, trip routes, and traffic management. A study quantified personal PM exposure in PVCs across 10 cities, finding higher exposure doses in less affluent cities and identifying key factors impacting PM levels. The findings are relevant to developing tropical cities characterized by socioeconomic discrepancies and inadequate transport infrastructures [42]. Furthermore, according to statistical findings by [93], wind significantly affects PM exposures, with variability across two-day periods and within modes. Brake systems, tire composition, ventilation systems, and tunnel depth were factors in metros, while wind speed and seasonality also impacted PM and CO levels. Though CO exposure in Hong Kong’s public transport was lower than in other cities, tunnel routes negatively affected in-cabin pollutant levels [81]. Traffic volume and routes also influenced in-cabin CO levels. The study identified traffic, self-pollution, number of stops, route, and speed as main drivers of in-cabin pollutants. Despite lower median BC levels, active modes resulted in higher exposure doses due to increased inhalation rates. The evaluation of in-vehicle CO levels highlighted severe health risks and the need for preventive measures during idling and traffic [77]. Travel mode, traffic load, and street configuration were found to affect dose and exposure in various mobility modes, with higher inhalation rates posing risks to pedestrians [78].
- ▪
- Inadequate amount or distribution of mass transit vehicles coupled with trip scheduling and inherent managerial issues enhancing overcrowding of tropic PVCs, as in trains, public buses and BRTs corroborate the need to improve mass transit vehicles for availability and ensure scheduling strategies to mitigate overcrowding tendencies. There is need to re-distribute vehicle categories towards the appropriate use concerning first and last mile deployment strategies, which can enhance sustainability, optimize energy intensity including ambient pollution risks besides other socio/economic and stakeholder benefits.
- ▪
- Inadequate ventilation systems and settings (including dependence solely on natural ventilation allowing unrestricted ingress of existential ambient pollution, inadequate HVAC systems in many public transport vehicles particularly in developing tropics) R Surveys conducted during hot-humid summers highlighted that travel mode, time of day, and background pollutant levels affected pollutant exposure variability. AC use was found to filter PM but not gaseous pollutants, emphasizing the need for fresh air dilution to reduce in-cabin levels [83]. A comparative study of personal PM2.5 exposures in two cities showed that newer vehicles with better ventilation technologies had lower PM levels [79].
IEQ Gaps and the Peculiarities of Developing Tropics and SSA Countries
4.3. RQ4: Mitigation Strategies to Combat IEQ Gaps of Tropical/Subtropical PVCs
5. Conclusions
Recommendations
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
Nomenclature
AC | Air Conditioned |
AC + FA | Air conditioning plus fresh air |
AC + EC | Air conditioning with external circulation |
AC + IC | Air conditioning with internal circulation |
AC + REC | Air conditioning plus recirculation |
AC | Acoustic comfort |
ACH | Air Changes per Hour |
AER | Air exchange rate |
AI | Artificial Intelligence |
AR | Auto rickshaw |
ASHRAE | American Society of Heating, Refrigerating and Air-Conditioning Engineers |
BC | Black Carbon |
BLDC | Brushless Direct Current |
BRT | Bus Rapid Transit |
BVFA | Bacteria, Viruses, Fungi, and Allergens |
CEI | Comprehensive Evaluation Index |
CFD | Computational Fluid Dynamics |
CNG | Compressed Natural Gas |
CO | Carbon Monoxide |
DI | Discomfort Index |
DOE | Design of Experiments |
eBC | Equivalent Black carbon |
EC | External Circulation |
EM | Experimental methods |
EV | Electric Vehicle |
FA | Fresh air |
HI | Heat Index |
HVAC | Heating, Ventilation, and Air Conditioning |
IAQ | Indoor Air Quality |
IC | Internal Circulation |
IEQ | Indoor Environmental Quality |
IoT | Internet of Things |
IR | Infrared |
ISO | International Organization for Standardization |
MEs | Micro-environments |
MLA | Machine learning algorithm |
MM | Mathematical models |
MRT | Mean Radiant Temperature |
NAC | Non-Air conditioned |
NV | Naturally Ventilated |
NVH | Noise vibration and Harshness |
NAAQS | National Ambient Air Quality Standards |
OEVF | Opened Exhaust Ventilation Fans |
OSHA | Occupational Safety and Health Administration |
PCM | Phase Change Material |
PAC | Portable air cleaner |
PE | Personal Exposure |
PM1 | Particulate Matter (1 μm) |
PM10 | Particulate Matter (10 μm) |
PM2.5 | Particulate Matter (2.5 μm) |
PMV | Predicted Mean Vote |
PN | Particle number |
PPD | Predicted Percentage Dissatisfied |
PRISMA | Preferred Reporting Items for Systematic Reviews and Meta-Analyses |
PVCs | Passenger Vehicle Cabins |
PVs | Passenger vehicles |
PWS | Partial Window Settings |
REC | Recirculation Mode |
RH | Relative Humidity |
RPC | Railway pantry car |
SET | Standard Effective Temperature |
SLR | Systematic Literature Review |
SSA | Sub-Saharan Africa |
Ta | Air Temperature |
Tcabin | Cabin Temperature |
Teq | Equivalent Temperature |
Tg | Globe Temperature |
Tr | Mean radiant temperature |
TRAP | Traffic-Related Air Pollution |
Ts | Surface Temperature |
TSI | Thermal Sensation Index |
TWS | Thermal Window Systems |
UFP | Ultrafine Particles |
UV | Ultraviolet |
Va | Air velocity |
VC | Visual Comfort |
VOCs | Volatile Organic Compounds |
WBGT | Wet-Bulb Globe Temperature |
WC | Windows Closed |
WHO | World Health Organization |
WO | Windows Open |
References
- Ogundiran, J.O.; Nyembwe, J.P.K.B.; Ribeiro, A.S.N.; Gameiro da Silva, M. Indoor Environmental Quality Assessment of Train Cabins and Passenger Waiting Areas: A Case Study of Nigeria. Sustainability 2023, 15, 16533. [Google Scholar] [CrossRef]
- Bandi, P.; Manelil, N.P.; Maiya, M.P.; Tiwari, S.; Thangamani, A.; Tamalapakula, J.L. Influence of flow and thermal characteristics on thermal comfort inside an automobile cabin under the effect of solar radiation. Appl. Therm. Eng. 2022, 203, 117946. [Google Scholar] [CrossRef]
- Lin, N.; Du, W.; Wang, J.; Yun, X.; Chen, L. The effect of COVID-19 restrictions on particulate matter on different modes of transport in China. Environ. Res. 2022, 207, 112205. [Google Scholar] [CrossRef]
- Chen, B.; Lian, Y.; Xu, L.; Deng, Z.; Zhao, F.; Zhang, H.; Liu, S. State-of-the-art thermal comfort models for car cabin Environment. Build. Environ. 2024, 262, 111825. [Google Scholar] [CrossRef]
- Trouve, M.; Lesteven, G.; Leurent, F. Private Motorization in Worldwide Developing Countries Metropolitan Areas: Patterns in the Early 21th Century; HAL Open Science: Arusha, France, 2018. [Google Scholar]
- Nyembwe, J.-P.K.B.; Ogundiran, J.O.; Chenari, B.; Simões, N.A.V.; Gameiro da Silva, M. The Indoor Climate of Hospitals in Tropical Countries: A Systematic Review. Energies 2023, 16, 3513. [Google Scholar] [CrossRef]
- Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G. Guidelines and Guidance Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef]
- Callander, E.J.; Topp, S.M. Health inequality in the tropics and its costs: A Sustainable Development Goals alert. Int. Health 2020, 12, 395–410. [Google Scholar] [CrossRef]
- Rodriguez, C.M.; D’Alessandro, M. Indoor thermal comfort review: The tropics as the next frontier. Urban Clim. 2019, 29, 100488. [Google Scholar] [CrossRef]
- Marcotullio, P.J.; Keßler, C.; Quintero Gonzalez, R.; Schmeltz, M. Urban Growth and Heat in Tropical Climates. Front. Ecol. Evol. 2021, 9, 616626. [Google Scholar] [CrossRef]
- Davey, T.H. Population Growth in The Tropics. Health Educ. J. 1948, 6, 150–154. [Google Scholar] [CrossRef]
- State of the Tropics Leadership Group. Sustainable Infrastructure in the Tropics; James Cook University: Townsville City, Australia, 2017; Available online: https://www.jcu.edu.au/__data/assets/pdf_file/0004/473503/SOTT-2017-Infrastructure-Report_V02.pdf (accessed on 4 December 2024).
- State of the Tropics Leadership Group. Health in The Tropics; James Cook University: Townsville City, Australia, 2019; Available online: https://www.jcu.edu.au/__data/assets/pdf_file/0012/864993/SOTT-Health-Report-2019-Webv02.pdf (accessed on 3 December 2024).
- Asia, Africa. Trends and Patterns of Urbanisation in The Urban Century. n.d.
- Gu, D.; Andreev, K.E.; Dupre, M. Major Trends in Population Growth Around the World. China CDC Wkly. 2021, 3, 604–613. [Google Scholar] [CrossRef] [PubMed]
- Khreis, H.; Warsow, K.M.; Verlinghieri, E.; Guzman, A.; Pellecuer, L.; Ferreira, A.; Jones, I.; Heinen, E.; Rojas-Rueda, D.; Mueller, N.; et al. The health impacts of traffic-related exposures in urban areas: Understanding real effects, underlying driving forces and co-producing future directions. J. Transp. Health 2016, 3, 249–267. [Google Scholar] [CrossRef]
- Ekpenyong, C.E.; Ettebong, E.O.; Akpan, E.E.; Samson, T.K.; Daniel, N.E. Urban city transportation mode and respiratory health effect of air pollution: A cross-sectional study among transit and non-transit workers in Nigeria. JBM Open 2012, 2, e001253. [Google Scholar] [CrossRef]
- Singh, V.; Agarwal, A. Variation of PM2.5 and inhalation dose across transport microenvironments in Delhi. Transp. Res. D Transp. Environ. 2024, 127, 104061. [Google Scholar] [CrossRef]
- Ravindra, K.; Agarwal, N.; Mor, S. Assessment of thermal comfort parameters in various car models and mitigation strategies for extreme heat-health risks in the tropical climate. J Environ. Manag. 2020, 267, 110655. [Google Scholar] [CrossRef] [PubMed]
- Rolle, A.; Schmandt, B.; Guinet, C.; Bengler, K. Assessment of Thermal Comfort in Different Vehicle Classes—The Suitability of ISO 14505-2:2006-12. In Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021), Online, 13–18 June 2021; Springer: Berlin/Heidelberg, Germany, 2021; pp. 806–813. [Google Scholar] [CrossRef]
- Okokon, E.O.; Taimisto, P.; Turunen, A.W.; Amoda, O.A.; Fasasi, A.E.; Adeyemi, L.G.; Juutilainen, J.; Lanki, T. Particulate air pollution and noise: Assessing commuter exposure in Africa’s most populous city. J. Transp. Health 2018, 9, 150–160. [Google Scholar] [CrossRef]
- Adon, M.; Yoboué, V.; Galy-Lacaux, C.; Liousse, C.; Diop, B.; Doumbia, E.H.T.; Gardrat, E.; Ndiaye, S.A.; Jarnot, C. Measurements of NO2, SO2, NH3, HNO3 and O3 in West African urban environments. Atmos. Environ. 2016, 135, 31–40. [Google Scholar] [CrossRef]
- Agbo, K.E.; Walgraeve, C.; Eze, J.I.; Ugwoke, P.E.; Ukoha, P.O.; Van Langenhove, H. A review on ambient and indoor air pollution status in Africa. Atmos. Pollut. Res. 2021, 12, 243–260. [Google Scholar] [CrossRef]
- Yin, X.; Thai, B.N.; Tan, Y.Q.; Salinas, S.V.; Yu, L.E.; Seow, W.J. When and where to exercise: An assessment of personal exposure to urban tropical ambient airborne pollutants in Singapore. Sci. Total Environ. 2024, 906, 167086. [Google Scholar] [CrossRef]
- Hanley, B.P.; Borup, B. Aerosol influenza transmission risk contours: A study of humid tropics versus winter temperate zone. Virol. J. 2010, 7, 98. [Google Scholar] [CrossRef] [PubMed]
- Knibbs, L.D.; Morawska, L.; Bell, S.C. The risk of airborne influenza transmission in passenger cars. Epidemiol. Infect. 2012, 140, 47420138. [Google Scholar] [CrossRef]
- Leitmeyer, K.; Adlhoch, C. Review Article. Epidemiology 2016, 27, 743–751. [Google Scholar] [CrossRef]
- Bertone, M.; Mikszewski, A.; Stabile, L.; Riccio, G.; Cortellessa, G.; D’Ambrosio, F.; Papa, V.; Morawska, L.; Buonanno, G. Assessment of SARS-CoV-2 airborne infection transmission risk in public buses. Geosci. Front. 2022, 13, 101398. [Google Scholar] [CrossRef]
- Mahmud, H.; Islam, M.; Khan, M.E.J.; Ahmed, D.H. Indoor thermal management of a public transport with phase change material (PCM). Energy Ecol. Environ. 2023, 8, 241–261. [Google Scholar] [CrossRef]
- Li, W.; Chen, J.; Lan, F. Environmental conditions driven method for automobile cabin pre-conditioning with multi-satisfaction objectives. PLoS ONE 2022, 17, e0266672. [Google Scholar] [CrossRef]
- Tamalapakula, J.L. In-Situ Studies on the Effect of Solar Control Glazings on In-Cabin Thermal Environment in Hot and Humid Climatic Zones; SAE Technical Paper; SAE International: Warrendale, PA, USA, 2020; Volume 2020. [Google Scholar] [CrossRef]
- Dodwad, A.; Nagarhalli, P.V.; Fartade, S.; Ahire, U.N. Improvement of AC System for Bus with Tropical/Hot Ambient Application; SAE Technical Paper; SAE International: Warrendale, PA, USA, 2023. [Google Scholar] [CrossRef]
- Kim, E.-B.; Park, J.-K.; Jung, W.-S. Estimation of Expected Temperature Using Heat Balance Model and Observation Data. Asian J. Atmos. Environ. 2015, 9, 214–221. [Google Scholar] [CrossRef]
- Orzechowski, T.; Skrobacki, Z. Evaluation of thermal conditions inside a vehicle cabin. EPJ Web Conf. 2016, 114, 02085. [Google Scholar] [CrossRef]
- Otuyo, M.K.; Nadzir, M.S.M.; Latif, M.T.; Din, S.A.M. A Review of Personal Exposure Studies in Asian Public Transport Microenvironments: Lessons Learned and Future Directions. Environ. Sci. Polut. Res. 2023. preprint. [Google Scholar] [CrossRef] [PubMed]
- Feng, C.; Ma, F.; Wang, R.; Li, W.; Gao, J. A thermal comfort evaluation on vehicular environments based on local human body thermal sensations. Res. Eng. 2023, 17, 100907. [Google Scholar] [CrossRef]
- Faber, J.; Brodzik, K. Air quality inside passenger cars. AIMS Environ. Sci. 2017, 4, 112–133. [Google Scholar] [CrossRef]
- Xu, B.; Chen, X.; Xiong, J. Air quality inside motor vehicles’ cabins: A review. Indoor Built Environ. 2018, 27, 452–465. [Google Scholar] [CrossRef]
- Zulauf, N.; Dröge, J.; Klingelhöfer, D.; Braun, M.; Oremek, G.M.; Groneberg, D.A. Indoor Air Pollution in Cars: An Update on Novel Insights. Int. J. Env. Res. Public Health 2019, 16, 2441. [Google Scholar] [CrossRef]
- ANSI/ASHRAE Standard 55-2020; Thermal Environmental Conditions for Human Occupancy. ASHRAE: Peachtree Corners, GA, USA, 2020.
- Manu, S.; Burgholz, T.M.; Nabilou, F.; Rewitz, K.; El-Mokadem, M.; Yadav, M.; Chinazzo, G.; Rupp, R.F.; Azar, E.; Syndicus, M.; et al. A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings. Build. Environ. 2024, 259, 111652. [Google Scholar] [CrossRef]
- Kumar, P.; Hama, S.; Abbass, R.A.; Nogueira, T.; Brand, V.S.; Abhijith, K.V.; Andrade, M.d.F.; Asfaw, A.; Aziz, K.H.; Cao, S.-J.; et al. Potential health risks due to in-car aerosol exposure across ten global cities. Environ. Int. 2021, 155, 106688. [Google Scholar] [CrossRef] [PubMed]
- Kumar, P.; Hama, S.; Nogueira, T.; Abbass, R.A.; Brand, V.S.; de Fatima Andrade, M.; Asfaw, A.; Aziz, K.H.; Cao, S.J.; El-Gendy, A.; et al. In-car particulate matter exposure across ten global cities. Sci. Total Environ. 2021, 750, 141395. [Google Scholar] [CrossRef]
- Pradhan, D.S.; Patra, A.K.; Santra, S.; Penchala, A.; Sahu, S.P.; Nazneen. In-cabin Particulate Matter Exposure of Heavy Earth Moving Machinery Operators in Indian Opencast Coal Mine. Aeroso. Sci. Eng. 2024, 1–18. [Google Scholar] [CrossRef]
- Tran, P.T.M.; Kalairasan, M.; Beshay, P.F.R.; Balasubramanian, R. In-car occupants’ exposure to airborne fine particles under different ventilation settings: Practical implications. Atmos. Environ. 2024, 318, 120271. [Google Scholar] [CrossRef]
- Charoenca, N.; Hamann, S.L.; Kungskulniti, N.; Sangchai, N.; Osot, R.; Kasemsup, V.; Ruangkanchanasetr, S.; Jongkhajornpong, P. Air Pollution inside Vehicles: Making a Bad Situation Worse. Int. J. Environ. Res. Public Health 2023, 20, 6970. [Google Scholar] [CrossRef]
- Odekanle, E.L.; Fakinle, B.S.; Jimoda, L.A.; Okedere, O.B.; Akeredolu, F.A.; Sonibare, J.A. In-vehicle and pedestrian exposure to carbon monoxide and volatile organic compounds in a mega city. Urban Clim. 2017, 21, 173–182. [Google Scholar] [CrossRef]
- Thanikachalam, G.; Selvam, D.K.; Raut, N.; Lakshmanan, R.; Reddy, R. Improving Cabin Comfort With Smart Auto-Flap HVAC Control. In Proceedings of the ITEC-India 2023—5th International Transportation Electrification Conference: eAMRIT—Accelerating e-Mobility Revolution for India’s Transportation, Chennai, India, 12–15 December 2023. [Google Scholar] [CrossRef]
- Aziz, S.A.A.; Gani, A.; Suhaimi, A.F.; Kalil, S.; Md Yusuf, A.Y.; Nuawi, M.Z. Noise exposure inside a passenger car cabin in tropical environmental condition. Def. ST Tech. Bull. 2017, 10, 290–296. [Google Scholar]
- ISO 5128:2023; Acoustics—Measurement of Interior Vehicle Noise. ISO: Geneva, Switzerland, 2023.
- Patel, D.; Shibata, T.; Wilson, J.; Maidin, A. Challenges in evaluating PM concentration levels, commuting exposure, and mask efficacy in reducing PM exposure in growing, urban communities in a developing country. Sci. Total Environ. 2016, 543, 416–424. [Google Scholar] [CrossRef] [PubMed]
- EN 16798-1:2019; Energy Performance of Buildings—Part 1: Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting, and Acoustics—Module M1-6. European Committee for Standardization: Brussels, Belgium, 2019.
- EN 13272-1:2019; Railway Applications—Electrical Lighting for Rolling Stock in Public Transport Systems. European Committee for Standardization: Brussels, Belgium, 2019.
- Othoman, M.A.; Fouzi, M.S.M.; Nordin, A. Assessment of thermal comfort in a car cabin under sun radiation exposure. In Engineering Applications for New Materials and Technologies; Advanced Structured Materials; Springer: Cham, Switzerland, 2018; Volume 85, pp. 469–479. [Google Scholar] [CrossRef]
- Pereira, F.L.; Silva, D.A.O.; Sopelete, M.C.; Sung, S.S.J.; Taketomi, E.A. Mite and cat allergen exposure in Brazilian public transport vehicles. Ann. Allergy Asthma Immunol. 2004, 93, 179–184. [Google Scholar] [CrossRef] [PubMed]
- Eldegwy, A.; Khalil, E.E. Passengers’ thermal comfort in private car cabin in hot climate. In Proceedings of the 2018 Joint Propulsion Conference, Cincinnati, OH, USA, 9–11 July 2018. [Google Scholar] [CrossRef]
- ANSI/ASHRAE Standard 55-2020; Thermal Environmental Conditions for Human Occupancy. ASHRAE: Peachtree Corners, GA, USA, 2021.
- ISO 7730:2005; Ergonomics of the Thermal Environment. ISO: Geneva, Switzerland, 2005.
- Khamis Mansour, M.; Musa, M.N.; Wan Hassan, M.N.; Saqr, K.M. Development of novel control strategy for multiple circuit, roof top bus air conditioning system in hot humid countries. Energy Convers. Manag. 2008, 49, 1455–1468. [Google Scholar] [CrossRef]
- EN 15251:2007; Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics. European Committee for Standardization: Brussels, Belgium, 2007.
- ISHRAE (Indian Society of Heating R and ACE). ISHRAE HVAC Handbook. Part 1—Air Conditioning; ISHRAE: Delhi, India, 2007. [Google Scholar]
- Alam, M.S.; Salve, U.R. Enhancement of thermal comfort inside the kitchen of non-airconditioned railway pantry car. Int. J. Heat Technol. 2021, 39, 275–291. [Google Scholar] [CrossRef]
- Ochiai, T.; Oda, S.; Sakai, M.; Ishiguro, S. Thin Ceiling Circulator to Enhance Thermal Comfort and Cabin Space; SAE Technical Papers; SAE International: Warrendale, PA, USA, 2019; Volume 2019. [Google Scholar] [CrossRef]
- ISO 7726:1998; Ergonomics of the Thermal Environment—Instruments for Measuring Physical Quantities. ISO: Geneva, Switzerland, 1998.
- ISO 14505:2006; Ergonomics of the Thermal Environment—Evaluation of Thermal Environments in Vehicles. ISO: Geneva, Switzerland, 2006.
- Duan, Z.; Wu, S.; Sun, H.; Lin, B.; Ding, P.; Cui, T.; To, J.; Zhang, X. Improvements in energy saving and thermal comfort for electric vehicles in summer through coupled electrochromic and radiative cooling smart windows. Build. Simul. 2024, 17, 1231–1251. [Google Scholar] [CrossRef]
- GB 7258-2017; Technical Specifications for Safety of Power-driven Vehicles Operating on Roads. Standards Press of China: Beijing, China, 2017.
- Bhateja, A. Impact of Different Types of Glazing on Thermal Comfort of Vehicle Occupants; SAE Technical Papers; SAE International: Warrendale, PA, USA, 2020; Volume 2020. [Google Scholar] [CrossRef]
- IS 2553-1 (1990); Safety Glass, Part 1: General Purpose. Bureau of Indian Standards (BIS): New Delhi, India, 1990.
- Kandasamy, N.; Kota, K.N.; Joshi, P. Numerical Evaluation of Vehicle Orientation and Glazing Material Impact on Cabin Climate and Occupant Thermal Comfort; SAE Technical Papers; SAE International: Warrendale, PA, USA, 2017; Volume 2017. [Google Scholar] [CrossRef]
- Hamid, M.K.A.; Singh, R.; Zain, M.Z.M.; Daud, Z.H.C.; Mazali, I.I.; Bakar, A.R.A. Experimental study on the improvement of thermal comfort inside a car cabin. In AIP Conference Proceedings; American Institute of Physics Inc.: College Park, MD, USA, 2023; Volume 2749. [Google Scholar] [CrossRef]
- Alam, M.S.; Arunachalam, M.; Salve, U.R. A pilot study on thermal comfort in Indian Railway pantry car chefs. J. Phys. Conf. Ser. 2019, 1240, 012033. [Google Scholar] [CrossRef]
- Ibrahim, F.; Ab Aziz, S.A. Study On Human Comfort of Military Vehicles in Malaysian Tropical Environment. Def. ST Tech. Bull. 2023, 16, 57–63. [Google Scholar]
- Luksamijarulkul, P.; Arunchai, N.; Luksamijarulkul, S.; Kaewboonchoo, O. Improving microbial air quality in air-conditioned mass transport buses by opening the bus exhaust ventilation fans. Southeast Asian J. Trop. Med. Public Health 2005, 36, 1032–1038. [Google Scholar] [PubMed]
- Kamiyo, O. Improving Thermal Comfort and Ventilation in Commercial Buses in Nigeria in Covid-19 Era. ABUAD J. Eng. Res. Dev. 2022, 5, 41–50. [Google Scholar]
- Alam, M.S.; Sharma, M.; Jadhav, G. Evaluating the influence of ambient conditions in the cooking space of railway pantry car using selected thermal indices and physiological parameter. Work 2024, 1–10, preprint. [Google Scholar] [CrossRef] [PubMed]
- Aswin Giri, J.; Karthikeyan, S.; Gokul Raj, M. Effect of ambient concentration of carbon monoxide (Co) on the in-vehicle concentration of carbon monoxide in chennai, india. Environ. Eng. Res. 2021, 26, 200165. [Google Scholar] [CrossRef]
- Betancourt, R.M.; Galvis, B.; Balachandran, S.; Ramos-Bonilla, J.P.; Sarmiento, O.L.; Gallo-Murcia, S.M.; Contreras, Y. Exposure to fine particulate, black carbon, and particle number concentration in transportation microenvironments. Atmos. Environ. 2017, 157, 135–145. [Google Scholar] [CrossRef]
- Castillo-Camacho, M.P.; Tunarrosa-Grisales, I.C.; Chacón-Rivera, L.M.; Guevara-Luna, M.A.; Belalcázar-Cerón, L.C. Personal Exposure to PM2.5 in the Massive Transport System of Bogota and Medellin, Colombia. Asian J. Atmos. Environ. 2020, 14, 210–224. [Google Scholar] [CrossRef]
- Carvalho, A.M.; Krecl, P.; Targino, A.C. Variations in individuals’ exposure to black carbon particles during their daily activities: A screening study in Brazil. Environ. Sci. Pollut. Res. 2018, 25, 18412–18423. [Google Scholar] [CrossRef]
- Targino, A.C.; Rodrigues, M.V.C.; Krecl, P.; Cipoli, Y.A.; Ribeiro, J.P.M. Commuter exposure to black carbon particles on diesel buses, on bicycles and on foot: A case study in a Brazilian city. Environ. Sci. Pollut. Res. 2018, 25, 1132–1146. [Google Scholar] [CrossRef] [PubMed]
- Shen, J.; Gao, Z. Commuter exposure to particulate matters in four common transportation modes in Nanjing. Build. Environ. 2019, 156, 156–170. [Google Scholar] [CrossRef]
- deSouza, P.; Lu, R.; Kinney, P.; Zheng, S. Exposures to multiple air pollutants while commuting: Evidence from Zhengzhou, China. Atmos. Environ. 2021, 247, 118168. [Google Scholar] [CrossRef]
- Targino, A.C.; Krecl, P.; Cipoli, Y.A.; Oukawa, G.Y.; Monroy, D.A. Bus commuter exposure and the impact of switching from diesel to biodiesel for routes of complex urban geometry. Environ. Pollut. 2020, 263, 114601. [Google Scholar] [CrossRef]
- Abbass, R.A.; Kumar, P.; El-Gendy, A. Car users exposure to particulate matter and gaseous air pollutants in megacity Cairo. Sustain. Cities Soc. 2020, 56, 102090. [Google Scholar] [CrossRef]
- Manojkumar, N.; Monishraj, M.; Srimuruganandam, B. Commuter exposure concentrations and inhalation doses in traffic and residential routes of Vellore city, India. Atmos. Pollut. Res. 2021, 12, 219–230. [Google Scholar] [CrossRef]
- Pant, P.; Habib, G.; Marshall, J.D.; Peltier, R.E. PM2.5 exposure in highly polluted cities: A case study from New Delhi, India. Environ. Res. 2017, 156, 167–174. [Google Scholar] [CrossRef] [PubMed]
- Sabapathy, A.; Saksena, S.; Flachsbart, P. Environmental justice in the context of commuters’ exposure to CO and PM10 in Bangalore, India. J. Expo. Sci. Environ. Epidemiol. 2015, 25, 200–207. [Google Scholar] [CrossRef]
- Tong, R.; Zhang, L.; Yang, X.; Zhou, P.; Xu, S. Probabilistic health risk of volatile organic compounds (VOCs): Comparison among different commuting modes in Guangzhou, China. Hum. Ecol. Risk Assess. 2019, 25, 637–658. [Google Scholar] [CrossRef]
- Gong, Y.; Wei, Y.; Cheng, J.; Jiang, T.; Chen, L.; Xu, B. Health risk assessment and personal exposure to Volatile Organic Compounds (VOCs) in metro carriages—A case study in Shanghai, China. Sci. Total Environ. 2017, 574, 1432–1438. [Google Scholar] [CrossRef] [PubMed]
- Xu, B.; Wu, Y.; Gong, Y.; Wu, S.; Wu, X.; Zhu, S.; Liu, T. Investigation of volatile organic compounds exposure inside vehicle cabins in China. Atmos. Pollut. Res. 2016, 7, 215–220. [Google Scholar] [CrossRef]
- Shiohara, N.; Fernández-Bremauntz, A.A.; Jiménez, S.B.; Yanagisawa, Y. The commuters’ exposure to volatile chemicals and carcinogenic risk in Mexico City. Atmos. Environ. 2005, 39, 3481–3489. [Google Scholar] [CrossRef]
- Gómez-Perales, J.E.; Colvile, R.N.; Nieuwenhuijsen, M.J.; Fernández-Bremauntz, A.; Gutiérrez-Avedoy, V.J.; Páramo-Figueroa, V.H.; Blanco-Jiménez, S.; Bueno-López, E.; Mandujano, F.; Bernabé-Cabanillas, R.; et al. Commuters’ exposure to PM2.5, CO, and benzene in public transport in the metropolitan area of Mexico City. Atmos Env. 2004, 38, 1219–1229. [Google Scholar] [CrossRef]
- Chan, L.Y.; Liu, Y.M. Carbon monoxide levels in popular passenger commuting modes traversing major commuting routes in Hong Kong. Atmos. Environ. 2001, 35, 2637–2646. [Google Scholar] [CrossRef]
- Maji, K.J.; Namdeo, A.; Hoban, D.; Bell, M.; Goodman, P.; Nagendra, S.S.; Barnes, J.; De Vito, L.; Hayes, E.; Longhurst, J.; et al. Analysis of various transport modes to evaluate personal exposure to PM2.5 pollution in Delhi. Atmos. Pollut. Res. 2021, 12, 417–431. [Google Scholar] [CrossRef]
- Gupta, S.K.; Elumalai, S.P. Exposure to traffic-related particulate matter and deposition dose to auto rickshaw driver in Dhanbad, India. Atmos. Pollut. Res. 2019, 10, 1128–1139. [Google Scholar] [CrossRef]
- Goel, R.; Gani, S.; Guttikunda, S.K.; Wilson, D.; Tiwari, G. On-road PM2.5 pollution exposure in multiple transport microenvironments in Delhi. Atmos. Environ. 2015, 123, 129–138. [Google Scholar] [CrossRef]
- Kolluru, S.S.R.; Patra, A.K.; Sahu, S.P. A comparison of personal exposure to air pollutants in different travel modes on national highways in India. Sci. Total Environ. 2018, 619–620, 155–164. [Google Scholar] [CrossRef]
- Gokul Raj, M.; Karthikeyan, S. Effect of modes of transportation on commuters’ exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in Chennai, India. Environ. Eng. Res. 2020, 25, 898–907. [Google Scholar] [CrossRef]
- Namdeo, A.; Ballare, S.; Job, H.; Namdeo, D. Commuter Exposure to Air Pollution in Newcastle, UK, and Mumbai, India. J. Hazard Toxic Radioact. Waste 2016, 20, A4014004. [Google Scholar] [CrossRef]
- Han, X.; Aguilar-Villalobos, M.; Allen, J.; Carlton, C.S.; Bayer, C.; Naeher, L.P. Traffic-related Occupational Exposures to PM2.5, CO, and VOCs in Trujillo, Peru. Int. J. Occup. Environ. Health 2005, 11, 276–288. [Google Scholar] [CrossRef] [PubMed]
- Saleel, C.A.; Mujeebu, M.A.; Algarni, S. Coconut oil as phase change material to maintain thermal comfort in passenger vehicles: An experimental analysis. J. Therm. Anal. Calorim. 2019, 136, 629–636. [Google Scholar] [CrossRef]
- Ohanuna, C.; Aigbe, D. Human Health Implications of Vehicular Indoor Air Pollution for Commuters in Selected Road Routes in Port Harcourt Metropolis. IIARD Int. J. Geogr. Environ. Manag. 2014, 10, 31–41. [Google Scholar] [CrossRef]
- Peiter, F.S.; Júnior, W.D.M. Indoor Environmental Quality: Sampling in One of the Sao Carlos’ Public Buses. OALibJ 2016, 3, 69120. [Google Scholar] [CrossRef]
- Regulatory Standard No. 15 (NR-15) 2017; Unhealthy Activities and Operations. Brazilian National Standards Organization: Rio de Janeiro, Brazil, 2017.
- Odekanle, E.L.; Fakinle, B.S.; Akeredolu, F.A.; Sonibare, J.A.; Adesanmi, A.J. Personal exposures to particulate matter in various modes of transport in Lagos city, Nigeria. Cogent. Environ. Sci. 2016, 2, 1260857. [Google Scholar] [CrossRef]
- Eghomwanre, A.F.; Tijani, A.Y.; Oguntoke, O. Air pollutant concentrations and comfort index in commercial buses within Abeokuta Metropolis, South-Western Nigeria. EQA Int. J. Environ. Qual. 2024, 64, 1–10. [Google Scholar] [CrossRef]
- Aziz, S.A.A.; Nuawi, M.Z.; Mohd Nor, M.J.; Daruis, D.D.I. Study of noise, vibration and harshness (NVH) for malaysian army (MA) 3-tonne trucks. Appl. Mech. Mater. 2014, 471, 74–80. [Google Scholar] [CrossRef]
- Ab Aziz, S.A.; Sohaimi, R.M.; Pu’ad, M.H.; Mohd Yaman, M.A. Noise, Vibration and Harshness (NVH) study on Malaysian Armed Forces (MAF) tactical vehicle. Appl. Mech. Mater. 2012, 165, 165–169. [Google Scholar] [CrossRef]
- Knibbs, L.D.; de Dear, R.J. Exposure to ultrafine particles and PM2.5 in four Sydney transport modes. Atmos. Environ. 2010, 44, 3224–3227. [Google Scholar] [CrossRef]
- Qiu, Z.; Song, J.; Xu, X.; Luo, Y.; Zhao, R.; Zhou, W.; Xiang, B.; Hao, Y. Commuter exposure to particulate matter for different transportation modes in Xi’an, China. Atmos. Pollut. Res. 2017, 8, 940–948. [Google Scholar] [CrossRef]
- Tan, S.H.; Roth, M.; Velasco, E. Particle exposure and inhaled dose during commuting in Singapore. Atmos. Environ. 2017, 170, 245–258. [Google Scholar] [CrossRef]
- Williams, R.D.; Knibbs, L.D. Daily personal exposure to black carbon: A pilot study. Atmos. Environ. 2016, 132, 296–299. [Google Scholar] [CrossRef]
- Javed, J.; Zahir, E.; Khwaja, H.A.; Khan, M.K.; Masood, S.S. Black Carbon Personal Exposure during Commuting in the Metropolis of Karachi. Atmosphere 2022, 13, 1930. [Google Scholar] [CrossRef]
- Li, B.; Lei, X.N.; Xiu, G.L.; Gao, C.Y.; Gao, S.; Qian, N.S. Personal exposure to black carbon during commuting in peak and off-peak hours in Shanghai. Sci. Total Environ. 2015, 524–525, 237–245. [Google Scholar] [CrossRef]
- Yang, F.; Kaul, D.; Wong, K.C.; Westerdahl, D.; Sun, L.; Ho, K.F.; Tian, L.; Brimblecombe, P.; Ning, Z. Heterogeneity of passenger exposure to air pollutants in public transport microenvironments. Atmos. Environ. 2015, 109, 42–51. [Google Scholar] [CrossRef]
- Chan, L.Y.; Lau, W.L.; Zou, S.C.; Cao, Z.X.; Lai, S.C. Exposure level of carbon monoxide and respirable suspended particulate in public transportation modes while commuting in urban area of Guangzhou, China. Atmos. Environ. 2002, 36, 5831–5840. [Google Scholar] [CrossRef]
- Wu, D.-L.; Lin, M.; Chan, C.-Y.; Li, W.-Z.; Tao, J.; Li, Y.-P.; Sang, X.-F.; Bu, C.-W. Influences of commuting mode, air conditioning mode and meteorological parameters on fine particle (PM2.5) exposure levels in traffic microenvironments. Aerosol. Air Qual. Res. 2013, 13, 709–720. [Google Scholar] [CrossRef]
- Tsai, D.H.; Wu, Y.H.; Chan, C.C. Comparisons of commuter’s exposure to particulate matters while using different transportation modes. Sci. Total Environ. 2008, 405, 71–77. [Google Scholar] [CrossRef]
- Chan, L.Y.; Lau, W.L.; Lee, S.C.; Chan, C.Y. Commuter exposure to particulate matter in public transportation modes in Hong Kong. Atmos. Environ. 2002, 36, 3363–3373. [Google Scholar] [CrossRef]
- Chan, L.Y.; Liu, Y.M.; Lee, S.C.; Chan, C.Y. Carbon monoxide levels measured in major commuting corridors covering different landuse and roadway microenvironments in Hong Kong. Atmos. Environ. 2002, 36, 255–264. [Google Scholar] [CrossRef]
- Anuar, M.H.K.; Jalaludin, J.; Suhaimi, N.F. Relationship Between Indoor Air Pollutants Exposure and Respiratory Symptoms Among Bus Drivers in a Malaysian Public University. Malays. J. Public Health Med. 2023, 23, 17–23. [Google Scholar] [CrossRef]
- Galvis, B. Nanoparticles on electric, gas, and diesel buses in mass transit buses of Bogotá Colombia. TeMA J. Land Use Mobil. Environ. 2023, 16, 367–381. [Google Scholar] [CrossRef]
- Kongtip, P.; Anthayanon, T.; Yoosook, W.; Onchoi, C. Exposure to particulate matter, CO2, CO, VOCs among bus drivers in Bangkok. J. Med. Assoc. Thai. 2012, 95 (Suppl. S6), S169–S178. [Google Scholar] [PubMed]
- Tong, Z.; Li, Y.; Westerdahl, D.; Adamkiewicz, G.; Spengler, J.D. Exploring the effects of ventilation practices in mitigating in-vehicle exposure to traffic-related air pollutants in China. Environ. Int. 2019, 127, 773–784. [Google Scholar] [CrossRef]
- Zhang, L.; Zhou, S.; Kwan, M.P.; Chen, F.; Dai, Y. The threshold effects of bus micro-environmental exposures on passengers’ momentary mood. Transp. Res. D Transp. Environ. 2020, 84, 102379. [Google Scholar] [CrossRef]
- GB/T 18883-2022; Standards for Indoor Air Quality. Standards Press of China: Beijing, China, 2022.
- Heberle, S.M.; Lorini, C.; Rosa, M.S.G.; Barros, N. Evaluation of bus driver exposure to nitrogen dioxide levels during working hours. Atmos. Environ. 2019, 216, 116906. [Google Scholar] [CrossRef]
- ISO/IEC 17025; Testing and Calibration Laboratories. ISO: Geneva, Switzerland, 2005.
- Mishra, S.S.; Gaba, V.K.; Netam, N. Effect of air velocity and relative humidity on passengers’ thermal comfort in naturally ventilated railway coach in hot-dry indian climate. Build. Environ. 2024, 254, 111421. [Google Scholar] [CrossRef]
- Lin, T.P.; Hwang, R.L.; Huang, K.T.; Sun, C.Y.; Huang, Y.C. Passenger thermal perceptions, thermal comfort requirements, and adaptations in short- and long-haul vehicles. Int. J. Biometeorol. 2010, 54, 221–230. [Google Scholar] [CrossRef] [PubMed]
- Zhou, X.; Liu, Y.; Luo, M.; Zheng, S.; Yang, R.; Zhang, X. Overall and thermal comfort under different temperature, noise, and vibration exposures. Indoor Air 2022, 32, e12915. [Google Scholar] [CrossRef] [PubMed]
- ISO 9886:2004; Ergonomics—Evaluation of Thermal Strain by Physiological Measurements. ISO: Geneva, Switzerland, 2004.
- Sarfaraz Alam, M.; Muthiah, A.; Salve, U. A Comparative Analysis Between Indoor and Outdoor Thermal Comfort Parameters of Railway Pantry Car. In Proceedings of International Conference on Thermofluids; Springer: Singapore, 2021; pp. 411–416. [Google Scholar] [CrossRef]
- Alam, M.S.; Muthiah, A.; Salve, U. A Field Investigation of the Average Indoor Thermal Comfort Parameters on the Railway Pantry Car Kitchen at the Different Cooking Period. In Design for Tomorrow—Volume 1; Smart Innovation, Systems and Technologies; Springer Science and Business Media: Singapore, 2021; Volume 221, pp. 203–212. [Google Scholar] [CrossRef]
- Alam, S.; Muthiah, A.; Salve, U.R. Appraisal of Thermal Comfort in Non-Air-conditioned and Air-conditioned Railway Pantry Car Kitchens. Int. J. Integr. Eng. 2020, 12, 318–327. [Google Scholar] [CrossRef]
- Shekhar Mishra, S.; Kumar Gaba, V.; Netam, N. Thermal comfort assessment of non air-conditioned railway coach in Central India during extreme summer. Therm. Sci. Eng. Prog. 2023, 46, 102206. [Google Scholar] [CrossRef]
- Alam, M.S.; Muthiah, A.; Salve, U.R. Thermal comfort of the kitchen in pantry cars on Indian railways. Instrum. Mes. Metrol. 2019, 18, 465–477. [Google Scholar] [CrossRef]
- Gong, Y.; Zhou, T.; Zhao, Y.; Xu, B. Characterization and risk assessment of particulate matter and volatile organic compounds in metro carriage in Shanghai, China. Atmosphere 2019, 10, 302. [Google Scholar] [CrossRef]
- GB 3095-2012; Ambient Air Quality Standards. Standards Press of China: Beijing, China, 2012.
- Both, A.F.; Westerdahl, D.; Fruin, S.; Haryanto, B.; Marshall, J.D. Exposure to carbon monoxide, fine particle mass, and ultrafine particle number in Jakarta, Indonesia: Effect of commute mode. Sci. Total Environ. 2013, 443, 965–972. [Google Scholar] [CrossRef]
- Tran, P.T.M.; Adam, M.G.; Tham, K.W.; Schiavon, S.; Pantelic, J.; Linden, P.F.; Sofianopoulou, E.; Sekhar, S.C.; Cheong, D.K.W.; Balasubramanian, R. Assessment and mitigation of personal exposure to particulate air pollution in cities: An exploratory study. Sustain. Cities Soc. 2021, 72, 103052. [Google Scholar] [CrossRef]
- Li, Z.; Che, W.; Frey, H.C.; Lau, A.K.H.; Lin, C. Characterization of PM2.5 exposure concentration in transport microenvironments using portable monitors. Environ. Pollut. 2017, 228, 433–442. [Google Scholar] [CrossRef]
- Kumar, P.; Gupta, N.C. Commuter exposure to inhalable, thoracic and alveolic particles in various transportation modes in Delhi. Sci. Total Environ. 2016, 541, 535–541. [Google Scholar] [CrossRef] [PubMed]
- Qiu, Z.; Cao, H. Commuter exposure to particulate matter in urban public transportation of Xi’an, China. J. Environ. Health Sci. Eng. 2020, 18, 451–462. [Google Scholar] [CrossRef]
- Saksena, S.; Quang, T.N.; Nguyen, T.; Dang, P.N.; Flachsbart, P. Commuters’ exposure to particulate matter and carbon monoxide in Hanoi, Vietnam. Transp. Res. D Transp. Env. 2008, 13, 206–211. [Google Scholar] [CrossRef]
- Yu, Q.; Lu, Y.; Xiao, S.; Shen, J.; Li, X.; Ma, W.; Chen, L. Commuters’ exposure to PM 1 by common travel modes in Shanghai. Atmos. Environ. 2012, 59, 39–46. [Google Scholar] [CrossRef]
- Liu, W.T.; Ma, C.M.; Liu, I.J.; Han, B.C.; Chuang, H.C.; Chuang, K.J. Effects of commuting mode on air pollution exposure and cardiovascular health among young adults in Taipei, Taiwan. Int. J. Hyg. Env. Health 2015, 218, 319–323. [Google Scholar] [CrossRef]
- Chau, C.K.; Tu, E.Y.; Chan, D.W.T.; Burnett, J. Estimating the total exposure to air pollutants for different population age groups in Hong Kong. Environ. Int. 2002, 27, 617–630. [Google Scholar] [CrossRef]
- Wong, L.T.; Mui, K.W.; Cheung, C.T.; Chan, W.Y.; Lee, Y.H.; Cheung, C.L. In-cabin exposure levels of carbon monoxide, carbon dioxide and airborne particulate matter in air-conditioned buses of Hong Kong. Indoor Built Environ. 2011, 20, 464–470. [Google Scholar] [CrossRef]
- Zhang, Y.; Yu, N.; Zhang, M.; Ye, Q. Particulate matter exposures under five different transportation modes during spring festival travel rush in China. Processes 2021, 9, 1133. [Google Scholar] [CrossRef]
- Kolluru, S.S.R.; Patra, A.K. Personal exposures to PM during short distance highway travel in India. Transp. Res. D Transp. Environ. 2020, 81, 102315. [Google Scholar] [CrossRef]
- EN 12341:2003; Ambient Air—Standard Gravimetric Measurement Method for the Determination of the PM10 or PM2.5 Mass Concentration of Suspended Particulate Matter. European Committee for Standardization: Brussels, Belgium, 2023.
- Che, W.W.; Frey, H.C.; Lau, A.K.H. Sequential Measurement of Intermodal Variability in Public Transportation PM2.5 and CO Exposure Concentrations. Environ. Sci. Technol. 2016, 50, 8760–8769. [Google Scholar] [CrossRef] [PubMed]
- Apte, J.S.; Kirchstetter, T.W.; Reich, A.H.; Deshpande, S.J.; Kaushik, G.; Chel, A.; Marshall, J.D.; Nazaroff, W.W. Concentrations of fine, ultrafine, and black carbon particles in auto-rickshaws in New Delhi, India. Atmos. Environ. 2011, 45, 4470–4480. [Google Scholar] [CrossRef]
- Luangprasert, M.; Vasithamrong, C.; Pongratananukul, S.; Chantranuwathana, S.; Pumrin, S.; De Silva, I.P.D. In-vehicle carbon dioxide concentration in commuting cars in Bangkok, Thailand. J. Air Waste Manag. Assoc. 2017, 67, 623–633. [Google Scholar] [CrossRef] [PubMed]
- Huang, H.L.; Hsu, D.J. Exposure levels of particulate matter in long-distance buses in Taiwan. Indoor Air 2009, 19, 234–242. [Google Scholar] [CrossRef] [PubMed]
- Guzman, L.A.; Beltran, C.; Morales, R.; Sarmiento, O.L. Inequality in personal exposure to air pollution in transport microenvironments for commuters in Bogotá. Case Stud. Transp. Policy 2023, 11, 100963. [Google Scholar] [CrossRef]
- Zahaba, M.; Kamaruddin, A.; Ariffin, A.; Tamsi, N.S.F.; Hassan, N. Indoor Air Quality (IAQ) Onboard a Naval Ship: A Comparative Study Between Compartments. Def. ST Tech. Bull. 2023, 16, 64–72. [Google Scholar]
- Anthayanon, T.; Kongtip, P.; Yoosook, W.; Sujirarat, D. Exposure to Fine Particles Among Bangkok Mass Transit Authority Bus Drivers. J. Health Res. 2011, 25, 5–10. [Google Scholar]
- Omagamre, E.W.; Ukpebor, J.E.; Ukpebor, E.E.; Okungbowa, G.E.; Odionye, E.H. Evaluation of In-Cabin Levels of Fine Particulates and Carbon Monoxide in Shuttle Buses Along a Major Intra-City Route in Benin City, Nigeria. Int. J. Renew. Energ. Environ. 2016, 2, 166–178. [Google Scholar]
- Shrestha, A.; Dhital, N.B. In-vehicle air quality in public buses during real-world trips in Kathmandu Valley, Nepal. Environ. Chall. 2024, 17, 101054. [Google Scholar] [CrossRef]
- Bryan, M.E.; Tempest, W.; Williams, D. Vehicle noise and the passenger. Appl. Ergon. 1978, 9, 151–154. [Google Scholar] [CrossRef]
- Edwards, N.J.; Widrick, R.; Wilmes, J.; Breisch, B.; Gerschefske, M.; Sullivan, J.; Potember, R.; Espinoza-Calvio, A. Reducing COVID-19 airborne transmission risks on public transportation buses: An empirical study on aerosol dispersion and control. Aerosol. Sci. Technol. 2021, 55, 1378–1397. [Google Scholar] [CrossRef]
- Wang, Q.; Gu, J.; An, T. The emission and dynamics of droplets from human expiratory activities and COVID-19 transmission in public transport system: A review. Build. Environ. 2022, 219, 109224. [Google Scholar] [CrossRef] [PubMed]
- Handayani, K.N.; Murtyas, S.; Wijayanta, A.T.; Hagishima, A. Thermal Comfort Challenges in Home-Based Enterprises: A Field Study from Surakarta’s Urban Low-Cost Housing in a Tropical Climate. Sustainability 2024, 16, 6838. [Google Scholar] [CrossRef]
- Shupler, M.; Tawiah, T.; Nix, E.; Baame, M.; Lorenzetti, F.; Betang, E.; Chartier, R.; Mangeni, J.; Upadhya, A.; de Cuevas, R.A.; et al. Household concentrations and female and child exposures to air pollution in peri-urban sub-Saharan Africa: Measurements from the CLEAN-Air(Africa) study. Lancet Planet Health 2024, 8, e95–e107. [Google Scholar] [CrossRef]
- Xu, J.; Xiang, Z.; Zhi, J.; Xu, X.; He, S.; Wang, J.; Du, Y.; Xu, G. Research on Virtual Simulation Evaluation System for Passenger Compartments Lighting of Subway Trains in China. In Advances in Human Factors in Wearable Technologies and Game Design; Ahram, T., Ed.; Springer: Cham, Switzerland, 2020; pp. 343–353. [Google Scholar]
- Albatayneh, A.M.; Assaf, M.N.; Albatayneh, A.; Assaf, M.N.; Alterman, D.; Jaradat, M. Comparison of the Overall Energy Efficiency for Internal Combustion Engine Vehicles and Electric Vehicles. Rigas Tehniskas Universitates Zinatniskie Raksti 2020, 24, 669–680. [Google Scholar] [CrossRef]
- Nyembwe, J.P.K.B.; Ogundiran, J.O.; Gameiro da Silva, M.; Albino Vieira Simões, N. Evaluation of Noise Level in Intensive Care Units of Hospitals and Noise Mitigation Strategies, Case Study: Democratic Republic of Congo. Buildings 2023, 13, 278. [Google Scholar] [CrossRef]
- Costa, M.F.; Landing, W.M.; Kehrig, H.A.; Barletta, M.; Holmes, C.D.; Barrocas, P.R.; Evers, D.C.; Buck, D.G.; Vasconcellos, A.C.; Hacon, S.S.; et al. Mercury in tropical and subtropical coastal environments. Environ. Res. 2012, 119, 88–100. [Google Scholar] [CrossRef] [PubMed]
- Croitoru, C.; Nastase, I.; Bode, F.; Meslem, A.; Dogeanu, A. Thermal comfort models for indoor spaces and vehicles—Current capabilities and future perspectives. Renew. Sustain. Energy Rev. 2015, 44, 304–318. [Google Scholar] [CrossRef]
- Khovalyg, D.; Kazanci, O.B.; Halvorsen, H.; Gundlach, I.; Bahnfleth, W.P.; Toftum, J.; Olesen, B.W. Critical review of standards for indoor thermal environment and air quality. Energy Build. 2020, 213, 109819. [Google Scholar] [CrossRef]
- ANSI/ASHRAE Standard 62.2-2016; Ventilation and Acceptable Indoor Air Quality in Residential Buildings. ASHRAE: Peachtree Corners, GA, USA, 2016.
- Ogundiran, J.; Nyembwe, J.-P.; Ribeiro, A.; da Silva, M. A Field Survey on Indoor Climate in Land Transport Cabins of Buses and Trains. Atmosphere 2024, 15, 589. [Google Scholar] [CrossRef]
- Hachem, M.; Saleh, N.; Paunescu, A.-C.; Momas, I.; Bensefa-Colas, L. Exposure to traffic air pollutants in taxicabs and acute adverse respiratory effects: A systematic review. Sci. Total Environ. 2019, 693, 133439. [Google Scholar] [CrossRef] [PubMed]
- Quagraine, V.; Boschi, N. Behavioral changes can help prevent indoor air-related illnesses in Ghana. Build. Environ. 2008, 43, 355–361. [Google Scholar] [CrossRef]
- Wang, B.; Zacharias, J. Noise, odor and passenger density in perceived crowding in public transport. Transp. Res. Part A Policy Pr. 2020, 135, 215–223. [Google Scholar] [CrossRef]
- Onyemaechi, N.; Ofoma, U. The public health threat of road traffic accidents in Nigeria: A call to action. Ann. Med. Health Sci. Res. 2016, 6, 199. [Google Scholar] [CrossRef] [PubMed]
No. | Research Questions (RQs) |
---|---|
RQ1 | To identify, present, evaluate, and characterize peer-reviewed published scientific studies concerning the IEQ of passenger transport vehicles in the tropics from 2000 to 2024, following the defined inclusion and exclusion SLR parameters. |
RQ2 | To discuss and characterize the studies identified in RQ1. |
RQ3 | To identify prevalent IEQ gaps, including the peculiarities of developing tropics and SSA countries affecting IEQ in PTV. |
RQ4 | To discuss IEQ gaps of RQ3 gaps for mitigation measures and strategies. |
Database | IEQ and Relevant Parameters | AND | Indoor Space Nomenclature | AND | Region and Climate | NOT | Excluded Nomenclatures |
---|---|---|---|---|---|---|---|
SCOPUS EBSCO | indoor climate OR indoor environment OR indoor environmental quality OR indoor air quality OR thermal comfort OR thermal sensation OR indoor pollution OR indoor air OR indoor light OR visual comfort OR indoor noise OR noise OR acoustic comfort OR passenger comfort OR particulate matter OR ultrafine particle OR black carbon OR volatile organic compound | AND | vehicle OR in-vehicle, in-cabin OR transport micro-environment OR mobile space OR bus OR train OR passenger train OR passenger coach OR passenger cabin, Bus Rapid Transit OR tram OR car OR passenger car OR Transport vehicle OR passenger compartment OR Public bus OR Metro bus OR mass transit vehicle OR passenger transport OR Public transport OR aircraft OR airplane OR aeroplane | AND | developing tropics OR developing tropical OR countries OR tropical countries OR tropics OR sub-Saharan countries OR sub-Saharan Africa OR hot-humid climate OR hot and humid climates OR tropical climate OR hot climates OR South America OR South Asia | NOT | building OR outdoor environment OR school building OR classroom OR office building OR hospital building OR home OR residential buildings OR commercial building |
No. | Inclusion Criteria | Exclusion Criteria |
---|---|---|
1 | Research studies published between the year 2000 and 2024. | All studies before the year 2000. |
2 | Written and published in English | Studies written in other languages |
3 | Only published scientific articles, book chapters, and technical and indexed peer-reviewed conference proceedings. | Thesis, Extended papers of an original paper. Dissertations, posters, reviews, demo documents, grey literature like reports, guidelines or laws |
4 | Within the defined scope of study, IEQ Studies for passenger transport vehicles, tropical and subtropical climate regions) | Studies outside the defined scope of review (unrelated to IEQ Studies for passenger transport vehicles in tropical climates and regions) |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Ogundiran, J.O.; Nyembwe, J.-P.K.B.; Ogundiran, J.; Ribeiro, A.S.N.; Gameiro da Silva, M. A Systematic Review of Indoor Environmental Quality in Passenger Transport Vehicles of Tropical and Subtropical Regions. Atmosphere 2025, 16, 140. https://doi.org/10.3390/atmos16020140
Ogundiran JO, Nyembwe J-PKB, Ogundiran J, Ribeiro ASN, Gameiro da Silva M. A Systematic Review of Indoor Environmental Quality in Passenger Transport Vehicles of Tropical and Subtropical Regions. Atmosphere. 2025; 16(2):140. https://doi.org/10.3390/atmos16020140
Chicago/Turabian StyleOgundiran, John Omomoluwa, Jean-Paul Kapuya Bulaba Nyembwe, James Ogundiran, Anabela Salgueiro Narciso Ribeiro, and Manuel Gameiro da Silva. 2025. "A Systematic Review of Indoor Environmental Quality in Passenger Transport Vehicles of Tropical and Subtropical Regions" Atmosphere 16, no. 2: 140. https://doi.org/10.3390/atmos16020140
APA StyleOgundiran, J. O., Nyembwe, J.-P. K. B., Ogundiran, J., Ribeiro, A. S. N., & Gameiro da Silva, M. (2025). A Systematic Review of Indoor Environmental Quality in Passenger Transport Vehicles of Tropical and Subtropical Regions. Atmosphere, 16(2), 140. https://doi.org/10.3390/atmos16020140