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.

Urban and regional ozone (O₃) pollution is a public health concern and causes damage to ecosystems. Due to the diverse emission sources of O₃ precursors and the complex interactions of air dispersion and chemistry, identifying the contributing sources of O₃ pollution requires integrated analysis to guide emission reduction plans. In this study, the meteorological characteristics leading to O₃ polluted days (in which the maximum daily 8–h average O₃ concentration is higher than the China Class II National O₃ Standard (160 μg/m³)) in Guangzhou (GZ, China) were analyzed based on data from 2019. The O₃ formation regimes and source apportionments under various prevailing wind directions were evaluated using a Response Surface Modeling (RSM) approach. The results showed that O₃ polluted days in 2019 could be classified into four types of synoptic patterns (i.e., cyclone, anticyclone, trough, and high pressure approaching to sea) and were strongly correlated with high ambient temperature, low relative humidity, low wind speed, variable prevailing wind directions. Additionally, the cyclone pattern strongly promoted O₃ formation due to its peripheral subsidence. The O₃ formation was nitrogen oxides (NOₓ)-limited under the northerly wind, while volatile organic compounds (VOC)-limited under other prevailing wind directions. Anthropogenic emissions contributed largely to the O₃ formation (54–78%) under the westerly, southwesterly, easterly, southeasterly, or southerly wind, but only moderately (35–47%) under the northerly or northeasterly wind. Furthermore, as for anthropogenic contributions, local emission contributions were the largest (39–60%) regardless of prevailing wind directions, especially the local NOₓ contributions (19–43%); the dominant upwind regional emissions contributed 12–46% (e.g., contributions from Dongguan were 12–20% under the southeasterly wind). The emission control strategies for O₃ polluted days should focus on local emission sources in conjunction with the emission reduction of upwind regional sources.

In this study, the spatiotemporal variabilities and characteristics of ozone (O₃) and fine particulate matter (PM₂.₅) were reconstructed, and the interaction between meteorological conditions and the co-occurrence of O₃ and PM₂.₅ in Zhuhai, a city in the Pearl River Delta (China), was analysed. The vertical distributions of lower tropospheric O₃, aerosol extinction coefficient, and wind velocity were measured using a ground-based LiDAR system. The diurnal variations in air pollutant concentrations and meteorological conditions at ground level were examined from 28 November to December 8, 2020 considering the weather conditions in Zhuhai. Heavy pollution episodes with increased concentrations of O₃ and PM₂.₅ were observed from 6 to 7 December after a period of cold air invasion. The maximum hourly average concentrations of O₃ and PM₂.₅ at the ground level reached up to 190 μg/m³, 98 μg/m³, respectively. The horizontal wind speed rapidly decreased to less than 2 m/s during the heavy pollution episodes driven by O₃ and PM₂.₅, whereas the vertical wind velocity was dominated by the downdraught. When the large-scale synoptic winds were weak, a strengthening sea breeze in the afternoon could promote the landward propagation of warm marine air masses, and a lower surface wind speed was driven by the convergence of cold air from the north and warm air from the south. In turn, this increased the residence time of air pollutants and promoted their conversion to secondary pollutants. Regarding the pollution sources, the results indicated that the Pearl River Estuary represented a ‘pool’ of O₃ and PM₂.₅ pollution. In addition, the contribution of regional pollutant transport could not be ignored when considering the accumulative increase in air pollution. Overall, the relatively weak synoptic winds, low mixing height, and high generation of pollution around Zhuhai collectively resulted in high concentrations of O₃ and PM₂.₅.

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.

Recent studies have shown that sub-lethal doses of herbicides may affect plant flowering, however, no study has established a direct relationship between the concentrations of deposited herbicide and plant flowering. Here the aim was to investigate the relationship between herbicide spray drift deposited on non-target plants and plant flowering in a realistic agro-ecosystem setting. The concentrations of the herbicide glyphosate deposited on plants were estimated by measuring the concentration of a dye tracer applied together with the herbicide. The estimated maximal and average deposition of glyphosate within the experimental area corresponded to 30 g glyphosate/ha (2.08% of the label rate of 1440 g a.i./ha) and 2.4 g glyphosate/ha (0.15% label rate), respectively, and the concentrations decreased rapidly with increasing distance from the spraying track. However, there were not a unique relation between distance and deposition, which indicate that heterogeneities of turbulence, wind speed and/or direction can strongly influence the deposition from 1 min to another during spraying. The effects of glyphosate on cumulative flower numbers and flowering time were modelled using Gompertz growth models on four non-target species. Glyphosate had a significantly negative effect on the cumulative number of flowers on Trifolium pratense and Lotus corniculatus, whereas there were no significant effects on Trifolium repens, and a positive, but non-significant, effect on number of flowers on Cichorium intybus. Glyphosate did not affect the flowering time of any of the four species significantly. Lack of floral resources is known to be of major importance for pollinator declines. The implications of the presented results for pesticide risk assessment are discussed.

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.

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.

Northern China is a significant source of dust source in Central Asia. Thus, high-resolution analysis of dust storms and comparison of dust sources in different regions of northern China are important to clarify the formation mechanism of East Asian dust storms and predict or even prevent such storms. Here, we analyzed spatiotemporal trends in dust storms that occurred in three main dust source regions during 1960–2007: Taklimakan Desert (western region [WR]), Badain Jaran and Tengger Deserts (middle region [MR]), and Otindag Sandy Land (eastern region [ER]). We analyzed daily dust storm frequency (DSF) at the 10-day scale (first [FTDM], middle [MTDM], and last [LTDM] 10 days of a month), and investigated the association of dust storm occurrences with meteorological factors. The 10-day DSF was greatest in the FTDM (accounting for 77.14% of monthly occurrences) in the WR, MTDM (45.85%) in the MR, and LTDM (72.12%) in the ER, showing a clear trend of movement from the WR to the ER. Temporal analysis of DSF revealed trend changes over time at annual and 10-day scales, with mutation points at 1985 and 2000. We applied single-factor and multiple-factor analyses to explore the driving mechanisms of DSF at the 10-day scale. Among single factors, a low wind-speed threshold, high solar radiation, and high evaporation were correlated with a high DSF, effectively explaining the variations in DSF at the 10-day scale; however, temperature, relative humidity, and precipitation poorly explained variations in DSF. Similarly, multiple-factor analysis using a classification and regression tree revealed that maximum wind speed was a major influencing factor of dust storm occurrence at the 10-day scale, followed by relative humidity, evaporation, and solar radiation; temperature and precipitation had weak influences. These findings help clarify the mechanisms of dust storm occurrence in East Asia.

Poyang Lake is the largest freshwater lake in China and a globally important wetland with various functions. Exploring the multidecadal trend of water quality and hydroclimatic conditions is important for understanding the adaption of the lake system under the pressure from multiple anthropogenic and meteorological stressors. The present study applied the Mann–Kendall trend analysis and Pettitt test to detect the trend and breakpoints of hydroclimatic, and water quality parameters (from the 1980s to 2018) and the trend of monthly–seasonal ammonia (NH₄-N) and total phosphorus (TP)concentrations (from 2002 to 2018) in Poyang Lake. Results showed that Poyang Lake had undergone a highly significant warming trend from 1980 to 2018, with a warming rate of 0.44 °C/decade in terms of annual daily mean air temperature. The wind speed and water level of the lake presented a highly significant decreasing trend, whereas no notable trend was detected for precipitation variations. The annual mean total nitrogen (TN), NH₄-N, TP, and permanganate index (CODMₙ) concentrations showed significant upward trends from the 1980s to 2018. Remarkable abrupt shifts were detected for TN, NH₄-N, and CODMₙ in around 2003. They were in accordance with the water level breakpoint of the lake, thus implying the important role of hydrological conditions in water quality variations in floodplain lakes. A significant increasing trend has been detected for Chl-a variations during wet season from 2008 to 2018, which could be attributed to the increasing trend of nutrient concentration during the nutrient-limited phase of Poyang Lake. These hydroclimatic and water quality trends suggest a high risk of increasing phytoplankton growth in Poyang Lake. This study thus emphasizes the need for adaptive lake eutrophication management for floodplain lakes, particularly the consideration of the strong trade-off and synergies between hydroclimatic conditions and water quality variations.

Most of the previous researches estimate influencing factors impact on air quality average without considering the heterogeneity of influential factors on different levels of air quality. In order to detect the different effects of influencing factors on air quality index (AQI) between lower-AQI and higher-AQI cities, this study applies a spatial quantile regression model (SQRM) to investigate heterogeneity of influential factors on AQI, while accounting for spatial autocorrelation of AQI. The results show that heterogeneity effects of windspeed, terrain slope, urbanization sprawl and spatial autocorrelation on AQI are large across the entire AQI spectrum, while heterogeneity effects of precipitation, temperature, relative humidity, terrain fluctuation and urbanization intensity on AQI are not obvious. The spatial positive autocorrelation of AQI in higher-AQI cities is greater than that in lower-AQI cities. Compared with higher-AQI cities, the negative impact of terrain slope on AQI is lager in lower-AQI cities. One unit increase in wind speed contributes AQI to decrease 9.31 to 5.64 then to 5.39 for lower, medium and higher-AQI cities. One unit increase in urbanization sprawl would lead AQI increase 25.6 to 15.6 then to 10.5 for lower, medium and higher-AQI cities. The heterogeneity analysis of meteorological, topographic and socioeconomic factors effects on air quality are of guiding significance for realizing the differentiation of policy measures for air pollution prevention and control.