Four regions of the Farahzad River Valley with different topography were selected to fully survey it and study the effects of morphology on local climate. then one of the hot days of the month of June 2021 (June 6th) was selected because the wind speeds increase in spring. According to the comparison of the simulation results with the existing site plans, the temperature in area 3 was the highest, 39.60 degrees, and the wind speed was 3.57 m/s. On the other hand, the study and analysis of the maps showed that the temperature of the roads in regions 3 and 4 were higher than the other two regions with a temperature range of 37.69-38.40, so the presence of impervious asphalt surfaces on the roads is very effective in increasing the air temperature in these areas.  Comparisons also showed that tall buildings and vegetation create shaded areas and increase wind speed. Based on this, two scenarios were designed. In the first scenario, doubling the height of buildings increased wind speed in Region 3 by 3.42 m/s and decreased temperatures by 1.59 degrees. In the second scenario, when tall trees were planted at certain distances around the streets, the temperature in Region 3 decreased by 1.68 degrees and the wind speed increased by 1.68 m/s. The results show that the differences in the topography of urban valleys cause ventilation of the environment and that the effect of this feature in other environments is more effective through planting than through buildings.

The influence of regional transport on aerosol pollution has been explored in previous studies based on numerical simulation or surface observation. Nevertheless, owing to inhomogeneous vertical distribution of air pollutants, vertical observations should be conducted for a comprehensive understanding of regional transport. Here we obtained the vertical profiles of aerosol and its precursors using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) at the Nancheng site in suburban Beijing on the southwest transport pathway of the Beijing-Tianjin-Hebei (BTH) region, China, and then estimated the vertical profiles of transport fluxes in the southwest-northeast direction. The maximum net transport fluxes per unit cross-sectional area, calculated as pollutant concentration multiply by wind speed, of aerosol extinction coefficient (AEC), NO₂, SO₂ and HCHO were 0.98 km⁻¹ m s⁻¹, 24, 14 and 8.0 μg m⁻² s⁻¹ from southwest to northeast, which occurred in the 200–300 m, 100–200 m, 500–600 m and 500–600 m layers, respectively, due to much higher pollutant concentrations during southwest transport than during northeast transport in these layers. The average net column transport fluxes were 1200 km⁻¹ m² s⁻¹, 38, 26 and 15 mg m⁻¹ s⁻¹ from southwest to northeast for AEC, NO₂, SO₂ and HCHO, respectively, in which the fluxes in the surface layer (0–100 m) accounted for only 2.3%–4.2%. Evaluation only based on surface observation would underestimate the influence of the transport from southwest cities to Beijing. Northeast or weak southwest transports dominated in clean conditions with PM₂.₅ <75 μg m⁻³ and intense southwest transport dominated in polluted conditions with PM₂.₅ >75 μg m⁻³. Southwest transport through the middle boundary layer was a trigger factor for aerosol pollution events in urban Beijing, because it not only directly bringing air pollutants, but also induced an inverse structure of aerosols, which resulted in stronger atmospheric stability and aggravated air pollution in urban Beijing.

The 2015 Paris agreement aims to cut greenhouse gas emissions and keep global temperature rise below 2 °C above pre-industrial levels. Reducing CH₄ emissions from leaking pipelines presents a relatively achievable objective. While walking and driving surveys are commonly used to detect leaks, the detection probability (DP) is poorly characterized. This study aims to investigate how leak rates, survey distance and speed, and atmospheric conditions affect the DP in controlled belowground conditions with release rates of 0.5–8.5 g min⁻¹. Results show that DP is highly influenced by survey speed, atmospheric stability, and wind speed. The average DP in Pasquill–Gifford stability (PG) class A is 85% at a low survey speed (2–11 mph) and decreases to 68%, 63%, 65%, and 60% in PGSC B/C, D, E/F, and G respectively. It is generally less than 25% at a high survey speed (22–34 mph), regardless of stability conditions and leak rates. Using the measurement data, a validated DP model was further constructed and showed good performance (R2: 0.76). The options of modeled favorable weather conditions (i.e., PG stability class and wind speed) to have a high DP (e.g., >50%) are rapidly decreased with the increase in survey speed. Walking survey is applicable over a wider range of weather conditions, including PG stability class A to E/F and calm to medium winds (0–5 m s⁻¹). A driving survey at a low speed (11 mph) can only be conducted under calm to low wind speed conditions (0–3 m s⁻¹) to have an equivalent DP to a walking survey. Only calm wind conditions in PG A (0–1 m s⁻¹) are appropriate for a high driving speed (34 mph). These findings showed that driving survey providers need to optimize the survey schemes to achieve a DP equivalence to the traditional walking survey.

Airborne fine particles can affect climate change and human health; moreover, they can be transported over significant distances. However, studies on characteristics of individual particles and their morphology, elemental composition, aging processes, and spatial distribution after long-range transport over the Yellow Sea are limited. Therefore, in this study, we conducted shipborne measurements of fine particulate matter of less than 2.5 μm in diameter (PM₂.₅) over the Yellow Sea and classified the individual particles into seven types based on their morphology and composition. Overall, the percentage of organic-rich particles was the highest, followed by that of sea spray, sulfur-rich, dust, metals, fly ash, soot, and other particles. Near Shandong, China, the percentage of fly ash and sulfur-rich particles increased, while an increased percentage of only sulfur-rich particles was observed near the Korean Peninsula. In the open sea, the PM₂.₅ concentrations were the lowest, and sea spray particles predominated. During the cruises, three types (Types 1, 2, and 3) of events with substantially increased PM₂.₅ concentrations occurred, each with different dominant particles. Type 1 events frequently featured air masses from northern China and Mongolia with high wind speeds and increased dust particles. Type 2 events involved air masses from China with high wind speeds; fly ash, soot, organic-rich particles, and the sulfate percentage in PM₂.₅ increased. Type 3 events displayed stagnant conditions and local transport (from Korea); soot, dust particles, and the secondary sulfate and nitrate percentages in PM₂.₅ increased. Thus, different types of transport affected concentrations and dominant types of fine particles over the Yellow Sea during spring.

The robust and eco-friendly super-hydrophobic sponge with remarkable performances has been potential adsorption material for the treatment of offshore oil spills. In this work, the durable PDMS@SiO₂@WS₂ sponge was fabricated via a green and facile one-step dipping method. The mixed tungsten disulfide (WS₂) microparticles and hydrophobic SiO₂ nanoparticles were immobilized on the sponge by non-toxic polydimethylsiloxane (PDMS) glue tier, which featured the hierarchical structure and extreme water repellency with the water contact angle of 158.8 ± 1.4°. The obtained PDMS@SiO₂@WS₂ sponge exhibits high oil adsorption capacity with 12–112 times of its own weight, and oil/water selectivity with separation efficiency over 99.85%. Notably, when subjected to the complex marine environment including high temperature, corrosive condition, insolation, and strong wind and waves, the modified sponge can maintain sable super-hydrophobicity with water contact angle over 150°. Moreover, it possesses superior mechanical stability for sustainable reusability and oil recovery. The sponge fabricated by non-toxic modifiers along with its sable super-hydrophobicity in complex marine environment makes it a potential material for practical applications.

Oil spills occurring either in oceans or inland waterways may cause serious economic losses and ecological damage. Previous studies pertaining to oil spills and their consequences are primarily based on marine environments, whereas few have focused on oil spills occurring in inland waterways characterised by pronounced flow advection transport effects, which differ from the marine environment. A generalised flume experiment is performed to investigate the spread and transport of oil spills, and the relationships between the area and thickness of oil slick over time are analysed parametrically. An oil spill model combined with a depth–integrated two–dimensional non–uniform flow model, which is suitable for modelling inland waterways based on the Lagrangian method, is established; it is calibrated and verified using measured data from the flume experiment. The model is applied to three scenarios on the Luoqi reach of the Yangtze River, and spilled oil drifting trajectory maps are obtained and analysed considering the field wind parameters. The results show that the drift distance of the oil slick in the inland waterway is primarily controlled by the flow velocity with effects of advection transport; however, the oil spill trajectory spreads toward the wind direction when the flow velocity is relatively small compared with the wind speed. The results of this study serve as a reference for predicting the spread and transport of oil spills in inland waterways.

Previous studies assessing excessive proliferation of phytoplankton (EPP) in lakes are generally based on single investigation and focused on limited environmental factors; meanwhile, less attention has been paid to lakes susceptibility to EPP. Here, we identify the priority of lakes for EPP control in a basin by assessing EPP in multiple lakes and identify the key factors related to lakes’ vulnerability to EPP. Field measurements, as well as multi-source survey data acquisition were conducted for 63 shallow lakes in the middle-lower Yangtze River basin. Resource-use efficiency by phytoplankton (RUE) was then used to represent lake susceptibility to EPP. Generalized linear models were used to assess the relative importance of environmental factors for RUE. We found that most lakes (76.19 %) were not suitable for recreation, due to health concern attributed to irritative or allergenic risk caused by EPP. Phosphorus was the primary limiting nutrient for EPP (74.60 % of lakes) which should be limited to < 0.09 mg/L. The linear model that included latitude, particulate matter 10, and precipitation explained 27.60 % of the variation of RUETP among lakes. In contrast, the linear model that included ozone, Secchi depth, and wind speed explained 19.41 % of the variation of RUETN among lakes. The key factor related to RUETP and RUETN was particulate matter 10 and ozone, respectively, both of which potentially increase RUE or reflect it. Our results suggest that integrating multiple survey datasets is critical for lakes EPP assessment in a basin, while lakes impacted by air pollution are a high priority for EPP control.

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.

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.

Poor air quality is an emerging problem in Australia primarily due to ozone pollution events and lengthening and more severe wildfire seasons. A significant deterioration in air quality was experienced in Australia’s most populous cities, Melbourne and Sydney, as a result of fires during the so-called Black Summer which ran from November 2019 through to February 2020. Following this period, social, mobility and economic restrictions to curb the spread of the COVID-19 pandemic were implemented in Australia. We quantify the air quality impact of these contrasting periods in the south-eastern states of Victoria and New South Wales (NSW) using a meteorological normalisation approach. A Random Forest (RF) machine learning algorithm was used to compute baseline time series’ of nitrogen dioxide (NO₂), ozone (O₃), carbon monoxide CO and particulate matter with diameter < 2.5 μm (PM₂.₅), based on a 19 year, detrended training dataset. Across Victorian sites, large increases in CO (188%), PM₂.₅ (322%) and ozone (22%) were observed over the RF prediction in January 2020. In NSW, smaller pollutant increases above the RF prediction were seen (CO 58%, PM₂.₅ 80%, ozone 19%). This can be partly explained by the RF predictions being high compared to the mean of previous months, due to high temperatures and strong wind speeds, highlighting the importance of meteorological normalisation in attributing pollution changes to specific events. From the daily observation-RF prediction differences we estimated 249.8 (95% CI: 156.6–343.) excess deaths and 3490.0 (95% CI 1325.9–5653.5) additional hospitalisations were likely as a result of PM₂.₅ and O₃ exposure in Victoria and NSW. During April 2019, when COVID-19 restrictions were in place, on average NO₂ decreased by 21.5 and 8% in Victoria and NSW respectively. O₃ and PM₂.₅ remained effectively unchanged in Victoria on average but increased by 20 and 24% in NSW respectively, supporting the suggestion that community mobility reduced more in Victoria than NSW. Overall the air quality change during the COVID-19 lockdown had a negligible impact on the calculated health outcomes.