Health impacts of air pollution in China

•Impacts of air pollution on various body systems health in China were highlighted. •China’s actions to control air pollution and their effects were briefly introduced. •Challenges and perspectives of the health effects of air pollution are provided. The health effects of air pollution have attracted considerable attention in China. In this review, the status of air pollution in China is briefly presented. The impacts of air pollution on the health of the respiratory system, the circulatory system, the nervous system, the digestive system, the urinary system, pregnancy and life expectancy are highlighted. Additionally, China’s actions to control air pollution and their effects are briefly introduced. Finally, the challenges and perspectives of the health effects of air pollution are provided. We believe that this review will provide a promising perspective on the health impacts of air pollution in China, and further elicit more attention from governments and researchers worldwide.     

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

The High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km³/year in 1985 to 18.2 km³/year in 2015, while irrigated croplands increased from 71,928 km² in 1985 to 78,464 km² in 2015 in the entire HPA. The hydroclimatic time-series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time-series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.     

沈阳地区臭氧污染日时空变化特征及天气分型研究

利用2013—2019年沈阳地区11个国控监测站近地层臭氧(O_3)浓度监测数据和地面气象观测资料,分析了沈阳地区O_3污染日的O_3浓度时空分布规律,并对造成O_3污染日的天气系统进行了主观分型。结果表明:自2013年以来,以O_3为首要污染物的天数逐年增加,2017年达到研究期内的最高值,但2018—2019年略有下降。O_3浓度的日变化趋势呈现明显的单峰形,O_3-1 h在10:00—20:00明显高于其他时间段,最大浓度值出现在15:00,而在01:00—07:00则相对较低。从季节变化上看,沈阳地区O_3污染主要发生在6—7月,两个月的O_3污染日之和占全年O_3总污染日的比例高达51%。从O_3浓度空间分布上看,沈阳地区三环外监测站测得的O_3浓度明显高于三环内监测站,高浓度区域主要集中在东部和东北部,城市中心存在明显的低浓度区,南部和北部差别不大,但也明显高于城市中心。造成沈阳地区O_3污染的主要天气类型有4种:暖脊型、均压场型、高空槽型和副热带高压型。其中:暖脊型出现的频次最高,占总样本的49.1%;副热带高压型出现的次数最少,占总样本的7.7%。     

三峡库区笋溪河流域面源污染及其与土壤可蚀性k值的关系

研究三峡库区面源污染特征及其与水土流失的关系,可为库区氮磷污染和土壤侵蚀控制提供依据.选择三峡库区库尾笋溪河流域,在流域内分园地、林地和耕地3种土地利用类型共采集126个土壤样品,并在主干和支流采集52个水质样品.根据EPIC模型计算土壤可蚀性k值,分析流域内土壤可蚀性k值对面源污染的影响.结果表明,笋溪河流域面源污染主要是氮污染,总氮均值达1.37 mg/L,氮素的主要形态为硝态氮,占总氮的71.2%;总磷浓度为0.1 mg/L.流域内土壤可蚀性k值均值为0.040,随着土层加深土壤可蚀性k值呈上升趋势;林地土壤可蚀性k值显著低于园地和耕地.笋溪河流域总氮浓度与园地和耕地0-20 cm土壤可蚀性k值有关,硝态氮浓度与耕地0-40 cm土壤可蚀性k值有关.因此,笋溪河流域面源污染严重,主要来源是耕地和园地,应实行免耕、植物篱等措施,同时减少化肥施用,增加有机肥比例,以增加土壤抗侵蚀能力,进而控制流域水土流失和面源污染.(图6参37)     

2016—2017年武汉市城区大气PM2.5污染特征及来源解析

利用2016年1月至2017年9月湖北省环境监测中心站大气复合污染自动监测站的在线监测数据，对武汉市城区PM_2.5的污染特征及主要来源进行解析。结果表明，武汉市城区PM_2.5质量浓度呈现出明显的季节差异，季节变化规律为冬季>春季>秋季>夏季。水溶性离子的主要成分SO₄^2-、NO₃^-和NH₄⁺占总离子质量浓度的82.0%。PM_2.5中阴离子相对阳离子较为亏损，颗粒整体呈碱性。夏季气态污染物的氧化程度较高且SO₂较NO₂氧化程度高。后向轨迹分析结果表明，区域传输是武汉市PM_2.5的一个重要来源，在4个典型重污染阶段，武汉市分别受到局地、东北、西北及西南方向气团传输的影响。PMF模型解析出武汉市PM_2.5五大主要来源及平均贡献率：扬尘22.0%、机动车排放27.7%、二次气溶胶21.6%、重油燃烧14.9%和生物质燃烧13.8%。     

新疆阿克苏地区平原区高砷地下水分布特征及富集因素分析

地下水砷污染是全球化环境问题.本文基于阿克苏地区平原区2017年75个地下水砷实测含量进行分析.结果表明,研究区地下水砷含量变化范围为ND—98.70μg·L^-1,平均值为9.42μg·L^-1,超标率达26.7%.水平方向上,高砷地下水主要集中在研究区的中部偏南一带;垂直方向上,山麓斜坡冲洪积砾质平原潜水区地下水砷含量平均值表现为深层潜水>浅层潜水,中下游河流冲积平原区承压水区地下水砷含量平均值表现为深层承压水>浅层承压水>潜水.采用绘制Piper三线图、Gibbs图、离子比例图等方法对研究区地下水砷的富集因素进行研究.结果表明,研究区地下水砷主要为自然来源;封闭的地质构造和造山带与河流等沉积环境相结合的水文地质条件有利于研究区地下水砷的富集;研究区高砷地下水水化学类型主要为HCO3·SO4-Na,还原性-弱碱性环境利于地下水砷富集;研究区地下水砷受强烈的蒸发浓缩作用进一步浓缩,同时地下水阴离子浓度增大加剧了地下水中阴离子与砷酸根、亚砷酸根之间的竞争吸附,利于地下水砷的富集.     

郑州市土壤与绿色植物中汞的分布特征

汞污染具有生物积累性,因而得到社会广泛关注。研究监测和评估了郑州市城区土壤和绿色植物叶片中汞浓度、分布、污染水平等。研究发现郑州市主城区土壤总汞浓度为0. 150～0. 958 mg/kg,平均浓度为0. 448 mg/kg;郑州市主城区绿色植物叶片总汞浓度为0. 017～0. 249 mg/kg,平均浓度为0. 107 mg/kg;土壤和叶片中汞浓度按功能区排序为交通枢纽区工业区商业区行政区高教区住宅区。采用地累积指数法对郑州市80个土壤样品的汞污染水平进行评估,结果显示60%受到轻度污染,35%受到偏中度污染,5%受到中度污染。研究较为全面地分析了土壤汞污染的现状及浓度,为郑州市土壤汞污染防治提供参考。     

典型产业承接区土壤砷含量的空间分布特征及影响因素

本文以揭阳市为研究区域,采集了1330个表层土壤(0—20 cm)样品和331个深层土壤(150—200 cm)样品,利用富集因子法分析了表层土壤中As的污染状况,通过GIS空间分析技术以及单因素分析法探究了土壤As的空间分布特征以及影响因素.结果表明,研究区表层土壤As含量的均值为6.03 mg·kg^-1,低于该区土壤背景值(7.16 mg·kg^-1)及农用地土壤污染风险管控值(20 mg·kg^-1),大部分土壤为轻微污染和中度污染.揭阳市表层土壤As含量高值区分布于揭阳市东北部、中部和西南部地区,低值区分布于西北部和东南部地区.土壤类型、成土母质和土地利用类型是影响表层土壤As含量的重要因素,在不同土壤类型中,黄壤和赤红壤As含量相对较高;不同成土母质中,粉砂岩母质土壤As含量显著高于其他母质;在不同土地利用类型中,农用地土壤As含量最高.     

石家庄市春季大气颗粒物的铅污染特征

为了解石家庄市2016年春季大气颗粒物的铅污染特征及来源,利用单颗粒气溶胶质谱仪(SPAMS),分析了大气中含铅颗粒的化学成分。结果表明: 研究期间大气环境中含铅颗粒数浓度共出现11次跳跃式升高,跳跃时间段内石家庄均处于轻度污染过程。从成分分析来看,含铅颗粒分为纯铅颗粒、Pb与K(Pb-K)、OC(Pb-OC)、Cl(Pb-Cl)、混合颗粒等八大类。观测结果表明:Pb-K颗粒最多,占到含铅颗粒的84.4%；其次为纯铅颗粒,占比为13.0%。与石家庄市污染源谱库比对进行来源解析,得到Pb-K颗粒主要来自生活垃圾焚烧源, 纯铅颗粒主要来自工业源。结合石家庄市大气污染源排放清单和后向气流轨迹分析,推测含铅颗粒可能来自市区西南方向某区县的生活垃圾焚烧企业。     

Assessment of deep aquifer groundwater quality in a geographically unique climatic region of Southern Western Ghats,India using water quality indices

Water quality index (WQI) models are generally used in hydrochemical studies to simplify complex data into single values to reflect the overall quality. In this study, deep groundwater quality in the Chittur and Palakkad Taluks of the Bharathapuzha river basin of Kerala, India, was assessed by employing the WQI method developed by the Canadian Council of Ministers of the Environment (CCME). The assessment of overall water quality is indispensable due to the specific characteristics of the study area, such as geography, climate, over-drafting, and prevalent agricultural practices. Forty representative samples were collected from the study area for monsoon (MON) and pre-monsoon (PRM) seasons. The results showed a general increase of contents from MON to PRM. The major cations were spread in the order Ca²⁺>Na+>Mg²⁺>K⁺ and the anions HCO₃⁻>Cl⁻>CO₃²⁻ based on their relative abundance. Among various parameters analysed, alkalinity and bicarbonate levels during MON were comparatively high, which is indicative of carbonate weathering, and 90% of the samples failed to meet the World Health Organization (WHO, 2017)/Bureau of Indian Standards (BIS, 2012) drinking water guidelines. The CCME WQI analysis revealed that nearly 50% of the samples during each season represented good and excellent categories. The samples in the poor category comprised 10% in MON and 15% in PRM. The overall WQI exhibited 15% of poor category samples as well. The spatial depiction of CCME WQI classes helped to expose zones of degraded quality in the centre to eastward parts. The spatial and temporal variations of CCME WQI classes and different physicochemical attributes indicated the influence of common factors attributing to the deep groundwater quality. The study also revealed inland salinity at Kolluparamba and Peruvamba stations, where agricultural activities were rampant with poor surface water irrigation.