| Literature DB >> 34793787 |
Mingyu Yang1, Lin Chen1, Goodluck Msigwa1, Kuok Ho Daniel Tang2, Pow-Seng Yap3.
Abstract
The impacts of COVID-19 on global environmental pollution since its onset in December 2019 require special attention. The rapid spread of COVID-19 globally has led countries to lock down cities, restrict traffic travel and impose strict safety measures, all of which have implications on the environment. This review aims to systematically and comprehensively present and analyze the positive and negative impacts of COVID-19 on global environmental pollution and carbon emissions. It also aims to propose strategies to prolong the beneficial, while minimize the adverse environmental impacts of COVID-19. It systematically and comprehensively reviewed more than 100 peer-reviewed papers and publications related to the impacts of COVID-19 on air, water and soil pollution, carbon emissions as well as the sustainable strategies forward. It revealed that PM2.5, PM10, NO2, and CO levels reduced in most regions globally but SO2 and O3 levels increased or did not show significant changes. Surface water, coastal water and groundwater quality improved globally during COVID-19 lockdown except few reservoirs and coastal areas. Soil contamination worsened mainly due to waste from the use of personal protective equipment particularly masks and the packaging, besides household waste. Carbon emissions were reduced primarily due to travel restrictions and less usage of utilities though emissions from certain ships did not change significantly to maintain supply of the essentials. Sustainable strategies post-COVID-19 include the development and adoption of nanomaterial adsorption and microbial remediation technologies, integrated waste management measures, "sterilization wave" technology and energy-efficient technologies. This review provides important insight and novel coverage of the environmental implications of COVID-19 in more than 25 countries across different global regions to permit formulation of specific pollution control and sustainability strategies in the COVID-19 and post-COVID-19 eras for better environmental quality and human health.Entities:
Keywords: Air pollution; COVID-19; Carbon emissions; Environmental pollution; Soil pollution; Water pollution
Mesh:
Substances:
Year: 2021 PMID: 34793787 PMCID: PMC8592643 DOI: 10.1016/j.scitotenv.2021.151657
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963
Fig. 1Flowchart of the five-step literature selection and review for this study.
Variations of air pollutants and particulates during and before lockdown worldwide.
| Pollutant | Area | Variations | Reference |
|---|---|---|---|
| PM2.5 | South Korea | March 2019: 37.37 ± 23.95 μg/m3 | ( |
| US | March 13 – April 8 2017–2019: 6.29 μg/m3 | ( | |
| Lahore, Pakistan | January 1 – March 22 2020: 176 μg/m3 | ( | |
| Kuala Lumpur, | January 1 – March 17, 2020: 18.6 μg/m3 | ( | |
| Kolkata, India | May 2019: 34.81 μg/m3 | ( | |
| Iraq | March 1–March 16 2020–38 μg/m3 | ( | |
| South Island, New Zealand | 2015–2019: 9.2 g/m3 | ( | |
| Sydney, Australia | April 2019: 8.52 ± 1.92 ppb | ( | |
| UK | 2013–2019: 11.17 μm/m3 | ( | |
| Lyon, France | Feb 2020: 12.1 μg/m3 | ( | |
| Nice, Italy | 2017–2019: 12.7 ± 0.9 μg/m3 | ( | |
| PM10 | South Korea | March 2019: 60.77 ± 31.05 μg/m3 | ( |
| Kuala Lumpur, Malaysia | January 1 – March 17, 2020: 24.3 μg/m3 | ( | |
| Kolkata, India | May 2019: 88.99 μg/m3 | ( | |
| Iraq | March 1 – March 16 2020: 132 μg/m3 | ( | |
| South Island, New Zealand | 2015–2019: 13.8 μg/m3 | ( | |
| Lyon, France | Feb 2020: 20.0 μg/m3 | ( | |
| Nice, Italy | 2017–2019: 25.7 ± 3.9 μg/m3 | ( | |
| NO2 | South Korea | March 2019: 20.38 ± 6.63 ppb | ( |
| US | March 13 – April 8 2017–2019: 18.68 ppb | ( | |
| Beijing-Tianjin-Hebei, China | February 2019: 9.3E+15 molecules/cm2 | ( | |
| Wuhan, China | February 2019: 1.5E+16 molecules/cm2 | ( | |
| Tokyo, Japan | February 2019: 9.8E+15 molecules/cm2 | ( | |
| Kuala Lumpur, Malaysia | January 1 – March 17, 2020: 12.1 ppb | ( | |
| Barcelona, Spain | (16/03–24/05/)2015–2019: 33.3 μg/m3 | ( | |
| Kolkata, India | May 2019: 16.48 μg/m3 | ( | |
| Iraq | March 1 – March 16 2020: 42 μg/m3 | ( | |
| South Island, New Zealand | 2015–2019: 19.7 μg/m3 | ( | |
| Sao Paulo, Brazil | May 2015–2019: 9.1E+15 molecules/cm2 | ( | |
| Sydney, Australia | April 2019: 8.91 ± 4.94 μg/m3 | ( | |
| UK | 2013–2019: 22.92 μm/m3 | ( | |
| Lyon, France | Feb 2020: 36.8 μg/m3 | ( | |
| Nice, Italy | 2017–2019: 34.0 ± 7.3 μg/m3 | ( | |
| Milan, Italy | February 7–20, 2020: 53.4 μg/m3 | ( | |
| CO | South Korea | March 2019: 0.513 ± 0.134 ppm | ( |
| Beijing-Tianjin-Hebei, China | February 2019: 3.23E+18 molecules/cm2 | ( | |
| Wuhan, China | February 2019: 3.51E+18 molecules/cm2 | ( | |
| Tokyo, Japan | February 2019: 2.51E+18 molecules/cm2 | ( | |
| Kuala Lumpur, Malaysia | January 1 – March 17, 2020: 0.88 ppm | ( | |
| Barcelona, Spain | (16/03–24/05/)2015–2019: 322.8 μg/m3 | ( | |
| Peru | March 6, 2020: 2.5 ppm | ( | |
| Kolkata, India | May 2019: 0.52 mg/m3 | ( | |
| Edmonton, Canada | March 2018: 0.14 ppm | ( | |
| O3 | South Korea | No change | ( |
| Kuala Lumpur, Malaysia | January 1 – March 17, 2020: 18.1 ppb | ( | |
| Barcelona, Spain | (16/03–24/05/)2015–2019: 85.3 μg/m3 | ( | |
| Peru | March 5, 2020: 0.1175 mol/m2 | ( | |
| Kolkata, India | May 2019: 31.92 μg/m3 | ( | |
| Iraq | March 1 – March 16 2020: 40 μg/m3 | ( | |
| UK | 2013–2019: 59.38 μm/m3 | ( | |
| Lyon, France | Feb 2020: 33.5 μg/m3 | ( | |
| Nice, Italy | 2017–2019: 62.6 ± 2.1 μg/m3 | ( | |
| SO2 | South Korea | No change | ( |
| Beijing-Tianjin-Hebei, China | February 2019: 1.3E+16 molecules/cm2 | ( | |
| Wuhan, China | February 2019: 3.9E+15 molecules/cm2 | ( | |
| Tokyo, Japan | February 2019: 2.7E+15 molecules/cm2 | ( | |
| Kuala Lumpur, Malaysia | January 1 – March 17, 2020: 0.89 ppb | ( | |
| Barcelona, Spain | (16/03–24/05/)2015–2019: 2.5 μg/m3 | ( | |
| Peru | March 5, 2020: 0.0002 mol/m2 | ( | |
| Kolkata, India | May 2019: 6.82 μg/m3 | ( | |
| UK | 2013–2019: 2.26 μm/m3 | ( | |
| HCHO | Beijing-Tianjin-Hebei, China | February 2019: 7.4E+15 molecules/cm2 | ( |
| Wuhan, China | February 2019: 7.3E+15 molecules/cm2 | ( | |
| Tokyo, Japan | February 2019: 3.9E+15 molecules/cm2 | ( | |
| Peru | March 5, 2020: 0.002 mol/m2 | ( |
Fig. 2Percent changes of air pollutants and particulates in different cities/countries during lockdown.
Air pollution and particulates measurement methods.
| S/no | Region | Methods | References |
|---|---|---|---|
| 1 | Asia-South Korea | Atmospheric monitoring stations | ( |
| 2 | Asia-Pakistan | TROPOspheric monitoring instrument/SAS software | ( |
| 3 | Asia-Malaysia | Continuous air quality monitoring station/Thermo Scientific Models 43i, 42i, 48i and 49i | ( |
| 4 | Asia-India | State Pollution Control Board/LANDSAT-8 OLI and LANDSAT-7 ETM | ( |
| 5 | Asia-China, South Korea and Japan | Satellite remote sensing | ( |
| 6 | North America-US | OpenAQ API | ( |
| 7 | South America-Brazil | Ozone monitoring instrument/air quality information systems | ( |
| 8 | South America-Peru | Sentinel-5 Precursor/VISAN tool | ( |
| 9 | North America-Canada | Monitoring station/Sentinel-5P satellite/MATLAB | ( |
| 10 | Europe-UK | Air-quality sensors/Met Office stations | ( |
| 11 | Europe-France | Monitoring stations | ( |
| 12 | Europe-Spain | Air quality monitoring (AQM) stations | ( |
| 13 | Europe-Italy | Meteorological control units/air quality control units | ( |
| 14 | Africa-Morocco | Air quality stations | ( |
| 15 | Africa-Nigeria | Integrated modeling of atmospheric composition/EGVOC-180 | ( |
| 16 | Africa-Egypt | Satellite monitoring | ( |
| 17 | Oceania-New Zealand | Stations/random forest algorithms | ( |
| 18 | Oceania-Australia | Monitoring stations/Vassarstat | ( |
Implications of COVID-19 on surface water pollution.
| Continents | Area | Impacts | Variations/key findings | Reference |
|---|---|---|---|---|
| Africa | Limpopo, Africa | ◆ | The temporal (2016–2019) trend of water quality shows a deteriorating trend. The Heavy Metals Pollution Index (HPI), Heavy Metals Evaluation Index (HEI) and Weighted Water Quality Index (WQI) have improved. | ( |
| Asia | Lucknow city,India | ◆ | The concentrations of all six heavy metals (As, Cd, Cr, Fe, Mn, Pb) in the Gomti River decreased significantly. The Heavy Metals Pollution Index (HPI) decreased at all sites and some of the observed areas were able to achieve a low pollution situation (HPI <15). | ( |
| Jiangsu, China | ◆ | Water quality parameters and fluorescent fraction intensities (WT-C1(20)) of the Beijing-Hangzhou Grand Canal decreased significantly. Gradual increase was observed after domestic outbreak was under control. | ( | |
| Turkey | ◆ | The concentrations of Cr, Ni, Zn, Cu, As, Pb, and Cd in the surface waters of the Merrick-Elgin River basin decreased significantly. Significant improvements in HPI and HEl were observed at all monitoring stations. | ( | |
| Nepal | ◆ | Dissolved oxygen (DO) levels improved by a factor of 1.5. Biological oxygen demand (BOD) and chemical oxygen demand (COD) decreased 1.5 times and 1.9 times, respectively. | ( | |
| Europe | Venice, Italy | ◆ | Due to the worldwide pandemic and the decrease in the number of tourists, the channels in Venice are now cleaner than before | ( |
| South and North America | São Paulo, Brazil | ◇ | Chlorophyll a (chl-a) and phycocyanin (PC) concentrations increased substantially in Guarapiranga and Billings reservoirs. It is worth noting that phycocyanin (PC) increased by almost 500%. | ( |
| Peru | ◆ | The PERMANOVA partition shows a strong and pronounced spatial effect of water quality variability. HPI shows that only 13.33% of the sampling area exceeds the critical pollution value (150). 86.67% of the sampling areas had low levels of cadmium pollution (<1). | ( | |
| Minnesota, USA | ◆ | Dissolved oxygen (DO) levels at sampling sites along the St. Louis River have increased, which is a good indicator of improved river water quality. There was also a trend of decreasing sediment in the river. | ( |
Note: ◆ indicates that COVID-19 has a positive impact on the pollution of surface water. ◇ indicates that COVID-19 has a negative effect on the contamination of surface water.
Implications of COVID-19 on coastal water pollution.
| Continents | Area | Impacts | Variations/key findings | Reference |
|---|---|---|---|---|
| Africa | Morocco | ◆ | The problem of serious bacterial contamination of Boukhalef water has been mitigated to some extent. The level of | ( |
| Kenya | ◆ | The amount of marine litter on beaches has been significantly reduced. Targeted interventions on beaches can significantly reduce marine litter pollution and thus improve the quality of coastal waters. | ( | |
| Asia | Pakistan | ◆ | Chl-a decreased from an average concentration of more than 10 mg/m3 to less than 5 mg/m3 in coastal areas of Pakistan, indicating a 50% decrease in Chl-a concentration in coastal areas. | ( |
| India | ◆ | The concentration of suspended matter (SPM) decreased by 15.48% and 37.50% in Chennai and Enore harbors, respectively. The diffuse attenuation coefficient Kd (490) showed a significant positive correlation with SPM. The reduction in SPM indicates the improvement in coastal water quality. The overall reduction in Chl-a in coastal waters indicates a net reduction in nutrient loading. | ( | |
| Europe | Cyprus | ◆ | Clean Coast Index (CCI), Waste Accumulation Rate (WAR) and Waste Accumulation Index (WAI) improved as a result of significant decreases in micro-, medium and large plastic concentrations on coastal waters. | ( |
| South and Central America | Ecuador | ◆ | Decreases in chlorophyll and attenuation coefficients Kd (490) indicate that the quality of the coastal environment has improved. More fish and large marine organisms were observed near the coast, which supports the improvement in the water quality of seawater. | ( |
| Belize | ◆ | The attenuation coefficient Kd (490) was used as an indicator of water quality, and a lower Kd (490) indicated increased water clarity. Heavy traffic areas (HTAs) showed a decreasing trend in Kd (490). | ( | |
| Argentina | ◇ | The misuse and mismanagement of personal protective equipment (PPE) and the significant increase in the production of masks and other products made of polymeric materials (gloves, protective clothing) have further contributed to plastic pollution in coastal waters. Anti-viral polymeric textile waste may also have long-term negative effects on the aquatic environment. | ( |
Note: ◆ indicates that COVID-19 has a positive impact on the pollution of coastal water. ◇ indicates that COVID-19 has a negative effect on the contamination of coastal water.
Fig. 3The variations of surface water pollution, coastal water pollution and groundwater pollution in different regions of the world during COVID-19.
Impacts of COVID-19 on solid waste generation, waste disposal, and soil contamination.
| Continents | Country | Population (approx.) | Total used masks (tonnes per day) | Urban population rate (%) | Total plastic packaging/shell (tonnes per day) | Total solid waste disposal (tonnes per day) | Solid waste disposal methods | Key findings | References |
|---|---|---|---|---|---|---|---|---|---|
| Asia | China | 1,439,323,776 | 5619.12 | 61% | 140.48 | 5759.60 | Incineration | The usual way to dispose these solid wastes in China is to incinerate them and provide heat to generate electricity. However, during the COVID-19 pandemic, the continued increase in solid wastes resulted in increased waste incineration, but the heat from incineration was not fully utilized. | ( |
| India | 1,380,004,385 | 3091.21 | 35% | 77.28 | 3168.49 | Incineration | Before masks are incinerated, it is recommended that used masks be disinfected with a civilian standard bleach solution (5%) or sodium hypochlorite solution (1%) before they are placed in a closed bin and given to a designated company for incineration. | ( | |
| Indonesia | 273,523,615 | 980.31 | 56% | 24.51 | 1004.82 | Incineration and landfill | These solid wastes are sanitized and labeled as hazardous. These wastes are taken to a designated site for incineration or landfill. | ( | |
| Pakistan | 220,892,340 | 494.80 | 35% | 12.37 | 507.17 | Incineration | These solid wastes are burned in the open area. The burning releases large amounts of toxic gases and substances that pollute the air and soil. | ( | |
| Bangladesh | 164,689,383 | 411.06 | 39% | 10.28 | 421.34 | Landfill | These discarded masks and other medical waste are dumped in large quantities in arbitrary places and are disposed of by untrained cleaning staff, and only a portion of the wastes are transported to the prescribed places for incineration. The pandemic has interrupted the activities of recovering and recycling of plastic waste, thus increasing the environmental pollution of landfills. | ( | |
| South and North America | Brazil | 212,559,417 | 1197.13 | 88% | 29.93 | 1227.06 | Landfill | Before the outbreak of COVID-19, the disposal of these wastes in Brazil was resource recovery. However, after the COVID-19 outbreak, these materials were disposed of in landfills and required an additional volume of 19,000 m3, which reduced the life of the landfills, with both economic and environmental losses. | ( |
| United States | 331,002,651 | 1758.29 | 83% | 43.96 | 1802.24 | Incineration and landfill | These solid wastes are handled as usual. However, the safety of the handling staff and the strict management of solid wastes are ensured. | ( | |
| Africa | Nigeria | 206,139,589 | 686.03 | 52% | 17.15 | 703.18 | Landfill | These wastes are dumped in and around landfills without proper disposal and it increases the risk of virus transmission. | ( |
Fig. 4Percent changes of carbon emissions around the world and their sources.