With the implementation of COVID-19 restrictions and consequent improvement in air quality due to the nationwide lockdown, ozone (O₃) pollution was generally amplified in China. However, the O₃ levels throughout the Guangxi region of South China showed a clear downward trend during the lockdown. To better understand this unusual phenomenon, we investigated the characteristics of conventional pollutants, the influence of meteorological and anthropogenic factors quantified by a multiple linear regression (MLR) model, and the impact of local sources and long-range transport based on a continuous emission monitoring system (CEMS) and the HYSPLIT model. Results show that in Guangxi, the conventional pollutants generally declined during the COVID-19 lockdown period (January 24 to February 9, 2020) compared with their concentrations during 2016–2019, while O₃ gradually increased during the resumption (10 February to April 2020) and full operation periods (May and June 2020). Focusing on Beihai, a typical Guangxi region city, the correlations between the daily O₃ concentrations and six meteorological parameters (wind speed, visibility, temperature, humidity, precipitation, and atmospheric pressure) and their corresponding regression coefficients indicate that meteorological conditions were generally conducive to O₃ pollution mitigation during the lockdown. A 7.84 μg/m³ drop in O₃ concentration was driven by meteorology, with other decreases (4.11 μg/m³) explained by reduced anthropogenic emissions of O₃ precursors. Taken together, the lower NO₂/SO₂ ratios (1.25–2.33) and consistencies between real-time monitored primary emissions and ambient concentrations suggest that, with the closure of small-scale industries, residual industrial emissions have become dominant contributors to local primary pollutants. Backward trajectory cluster analyses show that the slump of O₃ concentrations in Southern Guangxi could be partly attributed to clean air mass transfer (24–58%) from the South China Sea. Overall, the synergistic effects of the COVID-19 lockdown and meteorological factors intensified O₃ reduction in the Guangxi region of South China.

The increasing demand for fresh water coupled with the need to recycle water and nutrients has witnessed a global increase in wastewater irrigation. However, the development of antibiotic resistance hotspots in different environmental compartments, as a result of wastewater reuse is becoming a global health concern. The effect of irrigation water sources (wastewater, surface water, fresh water) on the presence and abundance of antibiotic resistance genes (ARGs) (blaCTX₋ₘ₋₃₂, tet-W, sul1, cml-A, and erm-B) and class 1 integrons (intI1) were investigated in the irrigation water-soil-crop continuum using quantitative real-time PCR (qPCR). Sul1 and blaCTX₋ₘ₋₃₂ were the most and least abundant ARGs in three environments, respectively. The abundance of ARGs and intI1 significantly decreased from wastewater to surface water and then fresh water. However, irrigation water sources had no significant effect on the abundance of ARGs and intI1 in soil and crop samples. Principal component analysis (PCA) showed that UV index and air temperature attenuate the abundance of ARGs and intI1 in crop samples whereas the air humidity and soil electrical conductivity (EC) promotes the ARGs and intI1. So that the climate condition of semi-arid regions significantly affects the abundance of ARGs and intI1 in crop samples. The results suggest that treated wastewater might be safely reused in agricultural practice in semi-arid regions without a significant increase of potential health risks associated with ARGs transfer to the food chain. However, further research is needed for understanding and managing ARGs transfer from the agricultural ecosystem to humans through the food chain.

Air and water quality at a concentrated animal feeding operation (CAFO) in Eastern North Carolina that uses a covered lagoon and anaerobic digester was evaluated for 2 weeks in August 2020. Real-time PM₂.₅ mass concentrations were determined using a reference ADR-1500 nephelometer and high-frequency measurements of dissolved inorganic nitrogen (DIN) were evaluated using autonomously logging sensors. Air and water quality parameters were assessed before, during and after wastewater from the lagoon was irrigated onto adjacent spray fields. Reference measurements were conducted alongside a HOBO weather station to collect real-time wind speed and direction, temperature, and humidity measurements. PM₂.₅ concentrations varied between 0 and 159 μg/m³ with an average concentration of 11 μg/m³, below EPA standard for secondary aerosols of 15 μg/m³. Higher PM₂.₅ concentrations were observed when wind originated from swine barns but not from covered lagoons. Water quality data showed that DIN concentrations downgradient from the CAFO were elevated relative to upstream concentrations. A groundwater seep that drains a spray field contained the highest average DIN concentration (31.0 ± 12.8 mg L⁻¹), which was 25 times greater than upstream DIN concentrations (1.2 ± 0.8 mg L⁻¹). Average DIN concentration at the downstream station was lower than the seep concentration (8.6 ± 16.2 mg L⁻¹), but approximately 8 times greater than upstream. Air quality data show that the lagoon cover was effective at mitigating air quality degradation, whereas DIN concentrations in water were similar to previous studies on CAFOs using open lagoons. In addition, air and water quality parameters were significantly (p < 0.001) higher after irrigation, indicating possible influence due to ammonia and nitrate elevation. Additional research is needed to compare high-frequency data collected from swine CAFOs using capped and uncapped lagoon systems to better understand spatiotemporal air and water quality trends of this practice.

Reduction of particulate matter (PM) has emerged as one of the most significant challenges in public health and environment protection worldwide. To address PM-related problems and effectively remove fine particulate matter (PM2.5), environmentalists proposed tree planting and afforestation as eco-friendly strategies. However, the PM removal effect of plants and its primary mechanism remains uncertain. In this study, we experimentally investigated the PM removal performance of five plant species in a closed chamber and the effects of relative humidity (RH) caused by plant evapotranspiration, as a governing parameter. On the basis of the PM removal test for various plant species, we selected Epipremnum aureum (Scindapsus) as a representative plant to identify the PM removal efficiency depending on evapotranspiration and particle type. Results showed that Scindapsus yielded a high PM removal efficiency for smoke type PM2.5 under active transpiration. We examined the correlation of PM removal and relative humidity (RH) and evaluated the increased effect of RH on PM2.5 removal by using a plant-inspired in vitro model. Based on the present results, the increase of RH due to evapotranspiration is crucial to the reduction of PM2.5 using plants.

The prevalence of allergic diseases has increased in the past few decades. Bio-aerosol proteins and their chemical modifications, such as 3-nitrotyrosine (3-NT), in the atmosphere have been attracting attention due to their promotive effects on allergies. 3-NT is generated from the amino acid, tyrosine, through a reaction with ozone (O3) and nitrogen dioxide (NO2). However, the underlying mechanisms have not yet been elucidated in detail. Therefore, we measured 3-NT and evaluated the relationships among 3-NT and various pollutants such as sulfur dioxide (SO2), NOx (NO + NO2), ozone (O3), PM7, total suspended particulate matter (TSP) containing proteins, humidity, and temperature. 3-NT positively correlated with O3, SO2, humidity, and temperature, and negatively correlated with NOx. A multiple regression analysis showed that 3-NT positively associated with O3, humidity, and PM7. O3 positively associated with 3-NT and PM7, and negatively associated with NOx and humidity. These results suggest that 3-NT is generated from PM proteins through a reaction with O3 under high humidity conditions, and that the measurement of 3-NT is important and useful for the research of O3.

Mercury (Hg) is a pervasive environmental contaminant that can impair avian health, consequently there is a need to gauge exposures. Bird blood provides a measure of recent dietary exposure to Hg, but blood collection and storage can be complex and costly. Dried blood spots (DBS) may help overcome challenges of whole blood analyses, therefore, this study aimed to develop and validate a novel method to assess Hg exposure in birds using DBS. First, accuracy and precision of blood Hg concentrations for entire DBS and DBS punches were determined for white leghorn chicken (Gallus gallus domesticus) dosed with methylmercury (MeHg) via egg injection. Next, we investigated Hg stability in chicken DBS subjected to time, temperature, and humidity treatments. Lastly, we applied the method to DBS created using standard field methods from zebra finch (Taeniopygia guttatato) in the laboratory and American golden-plover (Pluvalis dominica) sampled in the field. All samples were analyzed for total Hg (THg) using direct Hg analysis. Accuracy was determined by comparing DBS concentrations with those of corresponding whole blood and reported as percent recovery. Accuracy for entire chicken DBS was 101.8 ± 5.4%, while DBS punches revealed lower recovery (87.7 ± 4.0 to 92.4 ± 4.1%). There was little effect of time, temperature, and humidity storage treatments on Hg concentrations of DBS, with mean DBS THg concentrations within ±8% of whole blood (n = 10 treatments). For zebra finch, DBS punches were more accurate (93.7 ± 9.7%) compared to entire DBS (126.8 ± 19.4%). While for American golden-plover, entire DBS resulted in the most accurate THg concentrations (111.5 ± 7.6%) compared to DBS punches (edge: 115.4 ± 18.9%, interior: 131.4 ± 16.1%). Overall, results indicate that DBS analysis using direct Hg analysis can accurately evaluate Hg exposure in birds.

PM2.5 concentrations in a typical residential apartment in Beijing and immediately outside of the building were measured simultaneously during heating and non-heating periods. The objective was to quantitatively explore the relationship between indoor and outdoor PM2.5 concentrations. A statistical method for predicting indoor PM2.5 concentrations was proposed. Ambient PM2.5 concentrations were strongly affected by meteorological conditions, especially wind directions. A bimodal distribution was identified during the heating season due to the frequent and rapid transition between severe pollution events and clean days. Indoor PM2.5 concentrations were significantly correlated with outdoor PM2.5 concentrations but with 1–2 h delay, and the differences can be explained by ambient meteorological features, such as temperature, humidity, and wind direction. These results indicate the potential to incorporate indoor exposure features to the regional air quality model framework and to more accurately estimate the epidemiological relationship between human mortality and air pollution exposure.

Whatever the exposure route, chemical, physical and biological pollutants modify the whole organism response, leading to nerve, cardiac, respiratory, reproductive, and skin system pathologies. Skin acts as a barrier for preventing pollutant modifications. This review aims to present the available scientific models, which help investigate the impact of pollution on the skin. The research question was “Which experimental models illustrate the impact of pollution on the skin in humans?” The review covered a period of 10 years following a PECO statement on in vitro, ex vivo, in vivo and in silico models. Of 582 retrieved articles, 118 articles were eligible. In oral and inhalation routes, dermal exposure had an important impact at both local and systemic levels. Healthy skin models included primary cells, cell lines, co-cultures, reconstructed human epidermis, and skin explants. In silico models estimated skin exposure and permeability. All pollutants affected the skin by altering elasticity, thickness, the structure of epidermal barrier strength, and dermal extracellular integrity. Some specific models concerned wound healing or the skin aging process. Underlying mechanisms were an exacerbated inflammatory skin reaction with the modulation of several cytokines and oxidative stress responses, ending with apoptosis. Pathological skin models revealed the consequences of environmental pollutants on psoriasis, atopic dermatitis, and tumour development. Finally, scientific models were used for evaluating the safety and efficacy of potential skin formulations in preventing the skin aging process or skin irritation after repeated contact. The review gives an overview of scientific skin models used to assess the effects of pollutants. Chemical and physical pollutants were mainly represented while biological contaminants were little studied. In future developments, cell hypoxia and microbiota models may be considered as more representative of clinical situations. Models considering humidity and temperature variations may reflect the impact of these changes.

Urban Heat Island (UHI) is posing a significant challenge due to growing urbanisations across the world. Green infrastructure (GI) is popularly used for mitigating the impact of UHI, but knowledge on their optimal use is yet evolving. The UHI effect for large cities have received substantial attention previously. However, the corresponding effect is mostly unknown for towns, where appreciable parts of the population live, in Europe and elsewhere. Therefore, we analysed the possible impact of three vegetation types on UHI under numerous scenarios: baseline/current GI cover (BGI); hypothetical scenario without GI cover (HGI-No); three alternative hypothetical scenarios considering maximum green roofs (HGR-Max), grasslands (HG-Max) and trees (HT-Max) using a dispersion model ADMS-Temperature and Humidity model (ADMS-TH), taking a UK town (Guildford) as a case study area. Differences in an ambient temperature between three different landforms (central urban area, an urban park, and suburban residential area) were also explored. Under all scenarios, the night-time (0200 h; local time) showed a higher temperature increase, up to 1.315 °C due to the lowest atmospheric temperature. The highest average temperature perturbation (change in ambient temperature) was 0.563 °C under HGI-No scenario, followed by HG-Max (0.400 °C), BGI (0.343 °C), HGR-Max (0.326 °C) and HT-Max (0.277 °C). Furthermore, the central urban area experienced a 0.371 °C and 0.401 °C higher ambient temperature compared with its nearby suburban residential area and urban park, respectively. The results allow to conclude that temperature perturbations in urban environments are highly dependent on the type of GI, anthropogenic heat sources (buildings and vehicles) and the percentage of land covered by GI. Among all other forms of GI, trees were the best-suited GI which can play a viable role in reducing the UHI. Green roofs can act as an additional mitigation measure for the reduction of UHI at city scale if large areas are covered.

The present work describes spreading of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) at the tropical and temperate zones which are explained based on insolation energy, Particulate Matter (PM₂.₅), latitude, temperature, humidity, Population Density (PD), Human Development Index (HDI) and Global Health Security Index (GHSI) parameters. In order to analyze the spreading of SARS-CoV-2 by statistical data based on the confirmed positive cases which are collected between December 31, 2019 to April 25, 2020. The present analysis reveals that the outbreak of SARS-CoV-2 in the major countries lie on the Equator is 78,509 cases, the countries lie on the Tropic of Cancer is 62,930 cases (excluding China) and the countries lie on the Tropic of Capricorn is 22,842 cases. The tropical countries, which comes between the Tropic of Cancer and Tropic of Capricorn is reported to be 1,77,877 cases. The temperate zone countries, which are above and below the tropical countries are reported to be 25,66,171 cases so, the pandemic analysis describes the correlation between latitude, temperate zones, PM₂.₅ and local environmental factors. Hence, the temperature plays a pivotal role in the spreading of coronavirus at below 20 °C. The spreading of SARS-CoV-2 cases in Northern and Southern Hemispheres has inverse order against absorption of insolated energy. In temperate zone countries, the concentration of PM₂.₅ at below 20 μg/m³ has higher spreading rate of SARS-CoV-2 cases. The effect of insolation energy and PM₂.₅, it is confirmed that the spreading of SARS-CoV-2 is explained by dumb-bell model and solid/liquid interface formation mechanism. The present meta-analysis also focuses on the impact of GHSI, HDI, PD and PM₂.₅ on spreading of SARS-CoV-2 cases.