Water Table Depth Estimates over the Contiguous United States Using a Random Forest Model.

Water table depth (WTD) has a substantial impact on the connection between groundwater dynamics and land surface processes. Due to the scarcity of WTD observations, physically-based groundwater models are growing in their ability to map WTD at large scales; however, they are still challenged to represent simulated WTD compared to well observations. In this study, we develop a purely data-driven approach to estimating WTD at continental scale. We apply a random forest (RF) model to estimate WTD over most of the contiguous United States (CONUS) based on available WTD observations. The estimated WTD are in good agreement with well observations, with a Pearson correlation coefficient (r) of 0.96 (0.81 during testing), a Nash-Sutcliffe efficiency (NSE) of 0.93 (0.65 during testing), and a root mean square error (RMSE) of 6.87 m (15.31 m during testing). The location of each grid cell is rated as the most important feature in estimating WTD over most of the CONUS, which might be a surrogate for spatial information. In addition, the uncertainty of the RF model is quantified using quantile regression forests. High uncertainties are generally associated with locations having a shallow WTD. Our study demonstrates that the RF model can produce reasonable WTD estimates over most of the CONUS, providing an alternative to physics-based modeling for modeling large-scale freshwater resources. Since the CONUS covers many different hydrologic regimes, the RF model trained for the CONUS may be transferrable to other regions with a similar hydrologic regime and limited observations.

Meteorological factors, governmental responses and COVID-19: Evidence from four European countries.

With the global lockdown, meteorological factors are highly discussed for COVID-19 transmission. In this study, national-specific and region-specific data sets from Germany, Italy, Spain and the United Kingdom were used to explore the effect of temperature, absolute humidity and diurnal temperature range (DTR) on COVID-19 transmission. From February 1st to November 1st, a 7-day COVID-19 case doubling time (Td), meteorological factors with cumulative 14-day-lagged, government response index and other factors were fitted in the distributed lag nonlinear models. The overall relative risk (RR) of the 10th and the 25th percentiles temperature compared to the median were 0.0074 (95% CI: 0.0023, 0.0237) and 0.1220 (95% CI: 0.0667, 0.2232), respectively. The pooled RR of lower (10th, 25th) and extremely high (90th) absolute humidity were 0.3266 (95% CI: 0.1379, 0.7734), 0.6018 (95% CI: 0.4693, 0.7718) and 0.3438 (95% CI: 0.2254, 0.5242), respectively. While the DTR did not have a significant effect on Td. The total cumulative effect of temperature (10th) and absolute humidity (10th, 90th) on Td increased with the change of lag days. Similarly, a decline in temperature and absolute humidity at cumulative 14-day-lagged corresponded to the lower RR on Td in pooled region-specific effects. In summary, the government responses are important factors in alleviating the spread of COVID-19. After controlling that, our results indicate that both the cold and the dry environment also likely facilitate the COVID-19 transmission.

Association of air pollution with outpatient visits for respiratory diseases of children in an ex-heavily polluted Northwestern city, China.

BACKGROUND: A great number of studies have confirmed that children are a particularly vulnerable population to air pollution. METHODS: In the present study, 332,337 outpatient visits of 15 hospitals for respiratory diseases among children (0-13 years), as well as the simultaneous meteorological and air pollution data, were obtained from 2014 to 2016 in Lanzhou, China. The generalized additive model was used to examine the effects of air pollutants on children's respiratory outpatient visits, including the stratified analysis of age, gender and season. RESULTS: We found that PM2.5, NO2 and SO2 were significantly associated with the increased total respiratory outpatient visits. The increments of total respiratory outpatient visits were the highest in lag 05 for NO2 and SO2, a 10 µg/m3 increase in NO2 and SO2 was associated with a 2.50% (95% CI: 1.54, 3.48%) and 3.50% (95% CI: 1.51, 5.53%) increase in total respiratory outpatient visits, respectively. Those associations remained stable in two-pollutant models. Through stratification analysis, all air pollutants other than PM10 were significantly positive associated with the outpatients of bronchitis and upper respiratory tract infection. Besides, both NO2 and SO2 were positively related to the pneumonia outpatient visits. PM2.5 and SO2 were significantly related to the outpatient visits of other respiratory diseases, while only NO2 was positively associated with the asthma outpatients. We found these associations were stronger in girls than in boys, particularly in younger (0-3 years) children. Interestingly, season stratification analysis indicated that these associations were stronger in the cold season than in the transition or the hot season for PM10, PM2.5 and SO2. CONCLUSIONS: Our results indicate that the air pollution exposure may account for the increased risk of outpatient visits for respiratory diseases among children in Lanzhou, particularly for younger children and in the cold season.

Effects of temperature variation and humidity on the death of COVID-19 in Wuhan, China.

Meteorological parameters are the important factors influencing the infectious diseases such as severe acute respiratory syndrome (SARS) and influenza. This study aims to explore the association between Corona Virus Disease 2019 (COVID-19) deaths and weather parameters. In this study, we collected the daily death numbers of COVID-19, meteorological parameters and air pollutant data from 20 January 2020 to 29 February 2020 in Wuhan, China. Generalized additive model was applied to explore the effect of temperature, humidity and diurnal temperature range on the daily death counts of COVID-19. There were 2299 COVID-19 death counts in Wuhan during the study period. A positive association with COVID-19 daily death counts was observed for diurnal temperature range (r = 0.44), but negative association for relative humidity (r = -0.32). In addition, one unit increase in diurnal temperature range was only associated with a 2.92% (95% CI: 0.61%, 5.28%) increase in COVID-19 deaths in lag 3. However, both 1 unit increase of temperature and absolute humidity were related to the decreased COVID-19 death in lag 3 and lag 5, with the greatest decrease both in lag 3 [-7.50% (95% CI: -10.99%, -3.88%) and -11.41% (95% CI: -19.68%, -2.29%)]. In summary, this study suggests the temperature variation and humidity may also be important factors affecting the COVID-19 mortality.

Indoor air pollution from solid fuels and hypertension: A systematic review and meta-analysis.

Cardiovascular diseases (CVD) are leading global health issue. More studies have linked indoor air pollution from solid fuel usage to hypertension risk, a leading risk factor for CVD. We conducted a systematic review and meta-analysis of observational studies assessing the relationship of indoor air pollution from solid fuel with hypertension risk. Using a protocol standardized a priori, two independent reviewers searched PubMed, the Cochrane Library, Ovid MEDLINE, Web of Science and EMBASE for available studies published before Dec.1, 2019. A random effects model was used to analyse the pooled results. Out of 3740 articles, 47 were reviewed in depth and 11 contributing to this meta-analysis. The use of household solid fuel was significantly associated with an increased risk of hypertension (OR = 1.52, 95% CI = 1.26 to 1.85). The smoking-controlled group (OR = 2.38, 95% CI = 1.58 to 3.60) had greater effect size of hypertension than the uncontrolled group (OR = 1.11, 95% CI = 1.10 to 1.11). These findings implicate that indoor air pollution from solid fuel may be an important risk factor for hypertension.

Has the mortality risk declined after the improvement of air quality in an ex-heavily polluted Chinese city-Lanzhou?

Lanzhou, an ex-heavily polluted city, was awarded "The Award for Today's Transformative Step" in 2015 World Climate Conference at Paris for its great efforts on air quality improvement since 2012. However, the health benefits from this improvement remain unclear. Therefore, we collected time-series data covering deaths, weather variables and air pollutants during the two periods (2004-2009, 2014-2017) and fitted single-pollutant models using the generalized additive models to evaluate the change of mortality risks associated with air pollutants in Lanzhou. Results showed that the annual average concentrations of respirable particulate matter (PM10) and sulfur dioxide (SO2) dropped by 19.28% and 66.29%, while the nitrogen dioxide (NO2) increased by 16.61% in 2014-2017 compared to 2004-2009. During the period 2004-2009, we found a 10-µg/m3 increase in PM10 (lag 2), SO2 (lag 0-5) and NO2 (lag 0-5) were associated with mortality increments of 0.12% (95% CI: 0.01, 0.22), 0.86% (95% CI: 0.42, 1.31) and 1.29% (95% CI: 0.70, 1.90), respectively. During the period 2014-2017, the association between PM10 and daily deaths was not significant, but we observed a 10-µg/m3 increase in SO2 (lag 0-5) and NO2 (lag 4) were related to mortality increments of 4.23% (95% CI: 1.82, 6.70) and 0.85% (95% CI: 0.19, 1.52), respectively. From 2004-2009 to 2014-2017, we observed markedly decline of mortality risk due to PM10, but not SO2 or NO2. In conclusion, the mortality risk of PM10 in Lanzhou has declined obviously after the substantially improved air quality due to the enforcement of air pollution controlling policies.

The Impact of Cold and Heat on Years of Life Lost in a Northwestern Chinese City with Temperate Continental Climate.

Cold spells and heat waves in a changing climate are well known as great public-health concerns due to their adverse effects on human health. However, very few studies have quantified health impacts of heat and cold in the region of Northwestern China. The purpose of the present study was to evaluate the effects of cold and heat on years of life lost (YLL) in Lanzhou, a city with temperate continental climate. We compiled a daily dataset including deaths, weather variables, and air pollutants in Lanzhou, China, from 2014-2017. We used a distributed lag non-linear model to estimate single-day and cumulative effects of heat and cold on daily YLL. Results indicated that both cold and heat were associated with increased YLL for registered residents in Lanzhou. Estimated heat effects appeared immediately in the first two days, while estimated cold effects lasted over a longer period (up to 30 days). Cold significantly increased the YLL of all residents except for males and those with respiratory diseases (≥65 years). Our results showed that both heat and cold had more pronounced effects on cardiovascular diseases compared to respiratory diseases. Males might be more vulnerable to heat, while females might suffer more YLL from cold. The effects of cold or heat on the elderly might appear earlier and last longer than those for other age groups.