A Review on the Resistance and Accumulation of Heavy Metals by Different Microbial Strains

Heavy metals accumulated the earth crust and causes extreme pollution. Accumulation of rich concentrations of heavy metals in environments can cause various human diseases which risks health and high ecological issues. Mercury, arsenic, lead, silver, cadmium, chromium, etc. are some heavy metals harmful to organisms at even very low concentration. Heavy metal pollution is increasing day by day due to industrialization, urbanization, mining, volcanic eruptions, weathering of rocks, etc. Different microbial strains have developed very efficient and unique mechanisms for tolerating heavy metals in polluted sites with eco-friendly techniques. Heavy metals are group of metals with density more than 5 g/cm3. Microorganisms are generally present in contaminated sites of heavy metals and they develop new strategies which are metabolism dependent or independent to tackle with the adverse effects of heavy metals. Bacteria, Algae, Fungi, Cyanobacteria uses in bioremediation technique and acts a biosorbent. Removal of heavy metal from contaminated sites using microbial strains is cheaper alternative. Mostly species involved in bioremediation include Enterobacter and Pseudomonas species and some of bacillus species too in bacteria. Aspergillus and Penicillin species used in heavy metal resistance in fungi. Various species of the brown algae and Cyanobacteria shows resistance in algae.

Accumulation of heavy metal pollution caused by traffic in forest trees in the park of Kerey and Janibek Khans of the city of Nur-Sultan, Kazakhstan

Air quality in Nur-Sultan, the fast-growing new capital city of Kazakhstan, has been poorly investigated. This research was carried in Kerey and Janibek Khans Park in Nur-Sultan, the capital city of Kazakhstan, which is affected by “different traffic density” on the roads. Three different categories of contamination (i) high pollution (distance from the main road 10–15 m), (ii) moderate pollution (distance from the side road 15–30 m), and (iii) low pollution (distance from the source of contamination 30–80 m) at different levels resulting from urban transportation were examined. The aim of the study is to determine the pollution accumulation amounts of Ni, Cd, Pb, Cr, Li, Co, Fe, and Zn in five different tree species: Norway spruce (Picea abies /L./ H. Karst.), blue spruce (Picea pungens Engelm.), Scots pine (Pinus sylvestris L.,), Siberian larch (Larix sibirica Ledeb.), and silver birch (Betula pendula Roth). Significant differences in Ni, Cd, Pb, Cr, Li, Co, Fe, and Zn accumulation amounts were determined between three different parts of the park exposed to different levels of contamination. Approximately twice higher Ni, 2.3 times Cd, 3.3 times Pb, 2.7 times Co, 1.6 times Zn accumulation were determined in the area exposed to high pollution than in the parts of the park exposed to low pollution. Cd deposition in the area exposed to high contamination was higher in silver birch than in Scots pine and Norway spruce, while Cr and Co deposition values were higher in Norway spruce than in birch and Scots pine.

A Constrained Markovian Diffusion Model for Controlling the Pollution Accumulation

This work presents a study of a finite-time horizon stochastic control problem with restrictions on both the reward and the cost functions. To this end, it uses standard dynamic programming techniques, and an extension of the classic Lagrange multipliers approach. The coefficients considered here are supposed to be unbounded, and the obtained strategies are of non-stationary closed-loop type. The driving thread of the paper is a sequence of examples on a pollution accumulation model, which is used for the purpose of showing three algorithms for the purpose of replicating the results. There, the reader can find a result on the interchangeability of limits in a Dirichlet problem.

Cause analysis of PM2.5 pollution during the COVID-19 lockdown in Nanning, China

To analyse the cause of the atmospheric PM2.5 pollution that occurred during the COVID-19 lockdown in Nanning, Guangxi, China, a single particulate aerosol mass spectrometer, aethalometer, and particulate Lidar coupled with monitoring near-surface gaseous pollutants, meteorological conditions, remote fire spot sensing by satellite and backward trajectory models were utilized during 18–24 February 2020. Three haze stages were identified: the pre-pollution period (PPP), pollution accumulation period (PAP) and pollution dissipation period (PDP). The dominant source of PM2.5 in the PPP was biomass burning (BB) (40.4%), followed by secondary inorganic sources (28.1%) and motor vehicle exhaust (11.7%). The PAP was characterized by a large abundance of secondary inorganic sources, which contributed 56.1% of the total PM2.5 concentration, followed by BB (17.4%). The absorption Ångström exponent (2.2) in the PPP was higher than that in the other two periods. Analysis of fire spots monitored by remote satellite sensing indicated that open BB in regions around Nanning City could be one of the main factors. A planetary boundary layer-relative humidity-secondary particle matter-particulate matter positive feedback mechanism was employed to elucidate the atmospheric processes in this study. This study highlights the importance of understanding the role of BB, secondary inorganic sources and meteorology in air pollution formation and calls for policies for emission control strategies.

Vertical Characteristics of Pollution Transport in Hong Kong and Beijing, China

Transported pollution plays an important role in the atmospheric environment of eastern China. This study analyzed the characteristics of surface winds at different air quality levels using meteorological station observations of both wind and mass concentrations of particulate matter with aerodynamic diameters <2.5 μm (PM2.5) over Hong Kong and Beijing. In recent decades, wind directions at the surface exhibit a similar pattern for both good and poor air quality levels at all three stations, indicating a weak relationship between surface winds and air quality in Hong Kong. However, winds at a height of 1–2 km govern pollution accumulation. This dominant role is illustrated by a sudden change in wind direction within this layer and a simultaneous pollution accumulation stage on 8 January 2014. The controlling influence of winds at 1–2 km on both the deterioration and improvement of air quality is also supported by a distinct vertical wind distribution for all 21 monotonic increasing stages and 17 decreasing stages of PM2.5. In contrast, air pollution is transported to Beijing throughout the atmospheric layer that extends from the surface to a height of more than 3 km. This key difference may be due to variations in meteorology, topography, and emission sources between Hong Kong and Beijing. The results that layer of 1–2 km in Hong Kong and of surface to 3 km in Beijing is the height where pollution transport is most likely to occur are critical for forecasting severe haze episodes in eastern China.

Cause Analysis of PM2.5 pollution during the COVID-19 lockdown in Nanning, China

To analyze the cause of atmospheric PM2.5 pollution occurred during the COVID-19 lockdown in Nanning of Guangxi, China, Single Particulate Aerosol Mass Spectrometer, Aethalometer, Particulate Lidar, coupled with the monitoring of near-surface gaseous pollutants, meteorological conditions, remote fire spots sensing by satellite and Backward Trajectory Models were conducted during 18–24, Feb 2020. Three haze stages of pre-pollution period (PPP), pollution accumulation period (PAP) and pollution dissipation period (PDP) were identified. The dominant source of PM2.5 in PPP was biomass burning (BB) (40.4%), followed by secondary inorganics (28.1%) and motor vehicle exhaust (11.7%). The PAP was characterized by a large abundance of secondary inorganics, which contributed for 56.1% of the total PM2.5 concentration, followed by BB (17.4%). The absorption Ångström exponent (2.2) in PPP was higher than those of the other two periods. The analysis of fire spots monitored by remote satellite sensing indicated that open BB in regions around Nanning city could be one of the main facotrs matters. The planetary boundary layer-relative humidity-secondary particles matter-particulate matter positive feedback mechanism was employed to elucidate the atompheric process in this study. This study highlights the importance of understanding the role of BB and meteorology in air pollution formation to call for policy for emission control strategies.