Plant -microbe assisted emerging contaminants (ECs) removal and carbon cycling.

Continuous increase in the level of atmospheric CO2 and environmental contaminates has aggravated various threats resulting from environmental pollution and climate change. Research into plant -microbe interaction has been a central concern of ecology for over the year. However, despite the clear contribution of plant -microbe to the global carbon cycle, the role of plant -microbe interaction in carbon pools, fluxes and emerging contaminants (ECs) removal are still a poorly understood. The use of plant and microbes in ECs removal and carbon cycling is an attractive strategy because microbes operate as biocatalysts to remove contaminants and plant roots offer a rich niche for their growth and carbon cycling. However, bio-mitigation of CO2 and removal of ECs is still under research phase because of the CO2 capture and fixation efficiency is too low for industrial purposes and cutting-edge removal methods have not been created for such emerging contaminants.

A biochemical and morphological study with multiple linear regression modeling-based impact prediction of ambient air pollutants on some native tree species of Haldwani City of Kumaun Himalaya, Uttarakhand, India.

The current study was conducted around the province of Haldwani City, Uttarakhand, India, to understand the seasonal variation of ambient air pollutants (PM2.5, PM10, SO2, and NO2) and their impact on four tree species, i.e., neem (Azadirachta indica), mountain cedar (Toona ciliate), bottlebrush (Callistemon citrinus), and guava (Psidium guajava) during 2020-2021. Multiple linear regression (MLR)-based prediction analysis showed that the selected air quality variables (PM2.5, PM10, SO2, and NO2) had a significant impact on the biochemical responses of selected tree spp. including, pH, ascorbic acid (AA), total chlorophyll content (T. Chl.), relative water content (RWC), and dust deposition potential. In this, the coefficient of variance (R2) of the developed models was in the range of 0.70-0.98. The ambient air pollutants showed significant seasonal variations as depicted by using the air pollution tolerance index (APTI) and anticipated performance index (API). The tree species from polluted sites observed more pollution tolerance than the tree species from the control site. Regression analysis showed a significant positive association between the biochemical characteristics and APTI, with the highest influence by AA (R2 = 0.961) followed by T. Chl., RWC, and pH. The APTI and API score was observed as maximum for A. indica and minimum for C. citrinus. The impact of air pollutants on the morphology of foliar surface was investigated by the scanning electron microscopy (SEM) and recorded various dust deposition patterns, stomatal blockages, and damage of guard cells in the trees growing along the polluted site (S2). The present study can assist environmental managers to examine the pollution-induced variables and develop an effective green belt for combating air pollution in polluted areas.

Prediction models for evaluating the impacts of ambient air pollutants on the biochemical response of selected tree species of Haridwar, India.

This study aimed to assess the spatio-temporal impact of selected ambient air pollutants (SO2, NO2, PM10, and PM2.5) on the biochemical response of four tree species including Neem (Azadirachta indica), Mountain cedar (Toona ciliate), Bottlebrush (Callistemon citrinus), and Guava (Psidium guajava) in the province of Haridwar City, Uttarakhand, India. The study was performed in 2020 and 2021 over three selected sites (S1: institutional; S2: industrial; and S3: urban). Purposely, seasonal data of ambient air pollutants and biochemical parameters (ascorbic acid, carotenoid, chlorophyll, pH, relative water content, and dust load) of selected tree species were collected and analyzed using multiple linear regression (MLR) tool to develop prediction models. The results indicated that biochemical parameters of all tree species were negatively impacted by the polluted ambient air quality in the industrial and urban (S2 and S3) sites as compared to the non-polluted institutional (S1) site. The models were characterized by high prediction performance as indicated by the coefficient of determination (R2) values greater than 0.80. Moreover, A. indica was found to be more 'tolerant' based on the air pollution tolerance index (APTI) followed by T. ciliate, P. guajava, and C. citrinus. Similarly, the anticipated performance index (API) was reported higher for A. indica (75 to 81.25%) followed by T. ciliate (68.75 to 75.00%), P. guajava (56.25%), and C. citrinus (37.50%), respectively. This study revealed that the selected tree species are being negatively impacted by the induced pollutant exposure in the urban and industrial region of Haridwar, India which needs sufficient mitigation measures to conserve their diversities.