Life-Course Health Risk Assessment of PM2.5 Elements in China: Exposure Disparities by Species, Source, Age, Gender, and Location.

Key stages in people's lives have particular relevance for their health; the life-course approach stresses the importance of these stages. Here, we applied a life-course approach to analyze the health risks associated with PM2.5-bound elements, which were measured at three sites with varying environmental conditions in eastern China. Road traffic was found to be the primary source of PM2.5-bound elements at all three locations, but coal combustion was identified as the most important factor to induce both cancer risk (CR) and noncancer risk (NCR) across all age groups due to the higher toxicity of elements such as As and Pb associated with coal. Nearly half of NCR and over 90% of CR occurred in childhood (1-6 years) and adulthood (>18 years), respectively, and females have slightly higher NCR and lower CR than males. Rural population is found to be subject to the highest health risks. Synthesizing previous relevant studies and nationwide PM2.5 concentration measurements, we reveal ubiquitous and large urban-rural environmental exposure disparities over China.

Quantification of Diffusive Methane Emissions from a Large Eutrophic Lake with Satellite Imagery.

Lakes are major emitters of methane (CH4); however, a longstanding challenge with quantifying the magnitude of emissions remains as a result of large spatial and temporal variability. This study was designed to address the issue using satellite remote sensing with the advantages of spatial coverage and temporal resolution. Using Aqua/MODIS imagery (2003-2020) and in situ measured data (2011-2017) in eutrophic Lake Taihu, we compared the performance of eight machine learning models to predict diffusive CH4 emissions and found that the random forest (RF) model achieved the best fitting accuracy (R2 = 0.65 and mean relative error = 21%). On the basis of input satellite variables (chlorophyll a, water surface temperature, diffuse attenuation coefficient, and photosynthetically active radiation), we assessed how and why they help predict the CH4 emissions with the RF model. Overall, these variables mechanistically controlled the emissions, leading to the model capturing well the variability of diffusive CH4 emissions from the lake. Additionally, we found climate warming and associated algal blooms boosted the long-term increase in the emissions via reconstructing historical (2003-2020) daily time series of CH4 emissions. This study demonstrates the great potential of satellites to map lake CH4 emissions by providing spatiotemporal continuous data, with new and timely insights into accurately understanding the magnitude of aquatic greenhouse gas emissions.

Increased heat risk in wet climate induced by urban humid heat.

Cities are generally warmer than their adjacent rural land, a phenomenon known as the urban heat island (UHI). Often accompanying the UHI effect is another phenomenon called the urban dry island (UDI), whereby the humidity of urban land is lower than that of the surrounding rural land1-3. The UHI exacerbates heat stress on urban residents4,5, whereas the UDI may instead provide relief because the human body can cope with hot conditions better at lower humidity through perspiration6,7. The relative balance between the UHI and the UDI-as measured by changes in the wet-bulb temperature (Tw)-is a key yet largely unknown determinant of human heat stress in urban climates. Here we show that Tw is reduced in cities in dry and moderately wet climates, where the UDI more than offsets the UHI, but increased in wet climates (summer precipitation of more than 570 millimetres). Our results arise from analysis of urban and rural weather station data across the world and calculations with an urban climate model. In wet climates, the urban daytime Tw is 0.17 ± 0.14 degrees Celsius (mean ± 1 standard deviation) higher than rural Tw in the summer, primarily because of a weaker dynamic mixing in urban air. This Tw increment is small, but because of the high background Tw in wet climates, it is enough to cause two to six extra dangerous heat-stress days per summer for urban residents under current climate conditions. The risk of extreme humid heat is projected to increase in the future, and these urban effects may further amplify the risk.

Quantifying the contribution of evaporation from Lake Taihu to precipitation with an isotope-based method.

Moisture recycling plays a crucial role in regional hydrological budgets. The isotopic composition of precipitation has long been considered as a good tracer to investigate moisture recycling. This study quantifies the moisture recycling fractions (fr) in the Lake Taihu region using spatial variations of deuterium excess in precipitation (dP) and surface water vapour flux (dE). Results show that dP at a site downwind of the lake was higher than that at an upwind site, indicating the influence of lake moisture recycling. Spatial variations in dP after sub-cloud evaporation corrections were 2.3, 1.4 and 3.2 ‰, and dE values were 27.4, 32.3 and 31.4 ‰ for the first winter monsoon, the summer monsoon and the second winter monsoon, respectively. Moisture recycling fractions were 0.48 ± 0.13, 0.07 ± 0.03 and 0.38 ± 0.05 for the three monsoon periods, respectively. Both using the lake parameterization kinetic fractionation factors or neglecting sub-cloud evaporation would decrease fr, and the former has a larger influence on the fr calculation. The larger fr in the winter monsoon periods was mainly caused by lower specific humidity of airmasses but comparable moisture uptake along their trajectories compared to the summer monsoon period.

Development and Performance Evaluation of a Low-Cost Portable PM2.5 Monitor for Mobile Deployment.

The concentration of fine particulate matter (PM2.5) is known to vary spatially across a city landscape. Current networks of regulatory air quality monitoring are too sparse to capture these intra-city variations. In this study, we developed a low-cost (60 USD) portable PM2.5 monitor called Smart-P, for use on bicycles, with the goal of mapping street-level variations in PM2.5 concentration. The Smart-P is compact in size (85 × 85 × 42 mm) and light in weight (147 g). Data communication and geolocation are achieved with the cyclist's smartphone with the help of a user-friendly app. Good agreement was observed between the Smart-P monitors and a regulatory-grade monitor (mean bias error: −3.0 to 1.5 µg m−3 for the four monitors tested) in ambient conditions with relative humidity ranging from 38 to 100%. Monitor performance decreased in humidity > 70% condition. The measurement precision, represented as coefficient of variation, was 6 to 9% in stationary mode and 6% in biking mode across the four tested monitors. Street tests in a city with low background PM2.5 concentrations (8 to 9 µg m−3) and in two cities with high background concentrations (41 to 74 µg m−3) showed that the Smart-P was capable of observing local emission hotspots and that its measurement was not sensitive to bicycle speed. The low-cost and user-friendly nature are two features that make the Smart-P a good choice for empowering citizen scientists to participate in local air quality monitoring.

Nitrous oxide flux observed with tall-tower eddy covariance over a heterogeneous rice cultivation landscape.

Although croplands are known to be strong sources of anthropogenic N2O, large uncertainties still exist regarding their emission factors, that is, the proportion of N in fertilizer application that escapes to the atmosphere as N2O. In this study, we report the results of an experiment on the N2O flux in a landscape dominated by rice cultivation in the Yangtze River Delta, China. The observation was made with a closed-path eddy covariance system on a 70-m tall tower from October 2018 to December 2020 (27 months). Temperature and precipitation explained 78% of the seasonal and interannual variability in the observed N2O flux. The growing season (May to October) mean flux (1.14 nmol m-2 s-1) was much higher than the median flux found in the literature for rice paddies. The mean N2O flux during the observational period was 0.90 ± 0.71 nmol m-2 s-1, and the annual cumulative N2O emission was 7.6 and 9.1 kg N2O-N ha-1 during 2019 and 2020, respectively. The corresponding landscape emission factor was 3.8% and 4.6%, respectively, which were much higher than the IPCC default direct (0.3%) and indirect emission factors (0.75%) for rice paddies.

Using supervised learning to develop BaRAD, a 40-year monthly bias-adjusted global gridded radiation dataset.

Diffuse solar radiation is an important, but understudied, component of the Earth's surface radiation budget, with most global climate models not archiving this variable and a dearth of ground-based observations. Here, we describe the development of a global 40-year (1980-2019) monthly database of total shortwave radiation, including its diffuse and direct beam components, called BaRAD (Bias-adjusted RADiation dataset). The dataset is based on a random forest algorithm trained using Global Energy Balance Archive (GEBA) observations and applied to the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) dataset at the native MERRA-2 resolution (0.5° by 0.625°). The dataset preserves seasonal, latitudinal, and long-term trends in the MERRA-2 data, but with reduced biases than MERRA-2. The mean bias error is close to 0 (root mean square error = 10.1 W m-2) for diffuse radiation and -0.2 W m-2 (root mean square error = 19.2 W m-2) for the total incoming shortwave radiation at the surface. Studies on atmosphere-biosphere interactions, especially those on the diffuse radiation fertilization effect, can benefit from this dataset.

Crowdsourced air temperatures contrast satellite measures of the urban heat island and its mechanisms.

The ubiquitous nature of satellite data has led to an explosion of studies on the surface urban heat island (SUHI). Relatively few have simultaneously used air temperature measurements to compare SUHI with the canopy UHI (CUHI), which is more relevant to public health. Using crowdsourced citizen weather stations (>50,000) and satellite data over Europe, we estimate the CUHI and SUHI intensity in 342 urban clusters during the 2019 heat wave. Satellites produce a sixfold overestimate of UHI relative to station measurements (mean SUHI 1.45°C; CUHI 0.26°C), with SUHI exceeding CUHI in 96% of cities during daytime and in 80% at night. Using empirical evidence, we confirm the control of aerodynamic roughness on UHI intensity, but find evaporative cooling to have a stronger overall impact during this time period. Our results support urban greening as an effective UHI mitigation strategy and caution against relying on satellite data for urban heat risk assessments.

Ocean surface energy balance allows a constraint on the sensitivity of precipitation to global warming.

Climate models generally predict higher precipitation in a future warmer climate. Whether the precipitation intensification occurred in response to historical warming continues to be a subject of debate. Here, using observations of the ocean surface energy balance as a hydrological constraint, we find that historical warming intensified precipitation at a rate of 0.68 ± 0.51% K-1, which is slightly higher than the multi-model mean calculation for the historical climate (0.38 ± 1.18% K-1). The reduction in ocean surface albedo associated with melting of sea ice is a positive contributor to the precipitation temperature sensitivity. On the other hand, the observed increase in ocean heat storage weakens the historical precipitation. In this surface energy balance framework, the incident shortwave radiation at the ocean surface and the ocean heat storage exert a dominant control on the precipitation temperature sensitivity, explaining 91% of the inter-model spread and the spread across climate scenarios in the Intergovernmental Panel on Climate Change Fifth Assessment Report.

A highly agricultural river network in Jurong Reservoir watershed as significant CO2 and CH4 sources.

Freshwaters are receiving growing concerns on atmospheric carbon dioxide (CO2) and methane (CH4) budget; however, little is known about the anthropogenic sources of CO2 and CH4 from river network in agricultural-dominated watersheds. Here, we chose such a typical watershed and measured surface dissolved CO2 and CH4 concentrations over 2 years (2015-2017) in Jurong Reservoir watershed for different freshwater types (river network, ponds, reservoir, and ditches), which located in Eastern China and were impacted by agriculture with high fertilizer N application. Results showed that significantly higher gas concentrations occurred in river network (CO2: 112 ± 36 µmol L-1; CH4: 509 ± 341 nmol L-1) with high nutrient concentrations. Dissolved CO2 and CH4 concentrations were supersaturated in all of the freshwater types with peak saturation ratios generally occurring in river network. Temporal variations in the gas saturations were positively correlated with water temperature. The saturations of CO2 and CH4 were positively correlated with each other in river network, and both of these saturations were also positively correlated with nutrient loadings, and negatively correlated with dissolved oxygen concentration. The highly agricultural river network acted as significant CO2 and CH4 sources with estimated emission fluxes of 409 ± 369 mmol m-2 d-1 for CO2 and 1.6 ± 1.2 mmol m-2 d-1 for CH4, and made a disproportionately large, relative to the area, contribution to the total aquatic carbon emission of the watershed. Our results suggested the aquatic carbon emissions accounted for 6% of the watershed carbon budget, and fertilizer N and watersheds land use played a large role in the aquatic carbon emission.

Biases in open-path carbon dioxide flux measurements: Roles of instrument surface heat exchange and analyzer temperature sensitivity.

Eddy covariance (EC) measurements of ecosystem-atmosphere carbon dioxide (CO2) exchange provide the most direct assessment of the terrestrial carbon cycle. Measurement biases for open-path (OP) CO2 concentration and flux measurements have been reported for over 30 years, but their origin and appropriate correction approach remain unresolved. Here, we quantify the impacts of OP biases on carbon and radiative forcing budgets for a sub-boreal wetland. Comparison with a reference closed-path (CP) system indicates that a systematic OP flux bias (0.54 µmol m-2 s-1) persists for all seasons leading to a 110% overestimate of the ecosystem CO2 sink (cumulative error of 78 gC m-2). Two potential OP bias sources are considered: Sensor-path heat exchange (SPHE) and analyzer temperature sensitivity. We examined potential OP correction approaches including: i) Fast temperature measurements within the measurement path and sensor surfaces; ii) Previously published parameterizations; and iii) Optimization algorithms. The measurements revealed year-round average temperature and heat flux gradients of 2.9 °C and 16 W m-2 between the bottom sensor surfaces and atmosphere, indicating SPHE-induced OP bias. However, measured SPHE correlated poorly with the observed differences between OP and CP CO2 fluxes. While previously proposed nominally universal corrections for SPHE reduced the cumulative OP bias, they led to either systematic under-correction (by 38.1 gC m-2) or to systematic over-correction (by 17-37 gC m-2). The resulting budget errors exceeded CP random uncertainty and change the sign of the overall carbon and radiative forcing budgets. Analysis of OP calibration residuals as a function of temperature revealed a sensitivity of 5 µmol m-3 K-1. This temperature sensitivity causes CO2 calibration errors proportional to sample air fluctuations that can offset the observed growing season flux bias by 50%. Consequently, we call for a new OP correction framework that characterizes SPHE- and temperature-induced CO2 measurement errors.

Are nitrous oxide emissions indirectly fueled by input of terrestrial dissolved organic nitrogen in a large eutrophic Lake Taihu, China?

Lakes actively transform nitrogen (N) and emit disproportionately large amounts of N2O relative to their surface area. Studies have investigated the relative importance of denitrification or nitrification on N2O emissions; however, the linkage between N2O efflux and dissolved organic nitrogen (DON) and carbon (DOC) remains largely unknown. Long-term (2012-2017) seasonal field observations and a series of degradation experiments were used to unravel how DON composition impacts N2O emissions from Lake Taihu, China. In the northwestern part of the lake, large riverine inflow and high N2O emissions occur in all seasons (24.6 ± 25.2 µmol m-2 d-1), coincident with high levels of terrestrial DON and DOC here. The degradation of labile DON and DOC likely enhanced ammonification as supported by the correlations between NH4+-N and DON, DOC, a(350), and terrestrial humic-like C3. The area with large riverine inputs in the northwestern part of the lake was characterized by low DO which may enhance incomplete aerobic nitrification and incomplete denitrification, both leading to N2O production. Twenty days laboratory experiments indicated greater N2O production in the northwest inflow samples (N2O on day 20: 120.9 nmol L-1 and 17.3 nmol L-1 for bio- and photo-degradation samples, respectively) compared with the central lake samples (N2O on day 20: 20.3 nmol L-1 and 12.3 nmol L-1 for bio- and photo-degradation samples, respectively), despite both having low Chl-a. Our DON and DOC degradation experiments confirmed the occurrence of ammonification along with consumption of NH4+-N and thereafter NO3--N. Our results collectively suggest that terrestrial DON fueled ammonification, enhanced nitrification and incomplete denitrification, and thereby became an important contributor to the N2O efflux from Lake Taihu.

Environmental investments decreased partial pressure of CO2 in a small eutrophic urban lake: Evidence from long-term measurements.

Inland waters emit large amounts of carbon dioxide (CO2) to the atmosphere, but emissions from urban lakes are poorly understood. This study investigated seasonal and interannual variations in the partial pressure of CO2 (pCO2) and CO2 flux from Lake Wuli, a small eutrophic urban lake in the heart of the Yangtze River Delta, China, based on a long-term (2000-2015) dataset. The results showed that the annual mean pCO2 was 1030 ± 281 µatm (mean ± standard deviation) with a mean CO2 flux of 1.1 ± 0.6 g m-2 d-1 during 2000-2015, suggesting that compared with other lakes globally, Lake Wuli was a significant source of atmospheric CO2. Substantial interannual variability was observed, and the annual pCO2 exhibited a decreasing trend due to improvements in water quality driven by environmental investment. Changes in ammonia nitrogen and total phosphorus concentrations together explained 90% of the observed interannual variability in pCO2 (R2 = 0.90, p < 0.01). The lake was dominated by cyanobacterial blooms and showed nonseasonal variation in pCO2. This finding was different from those of other eutrophic lakes with seasonal variation in pCO2, mostly because the uptake of CO2 by algal-derived primary production was counterbalanced by the production of CO2 by algal-derived organic carbon decomposition. Our results suggested that anthropogenic activities strongly affect lake CO2 dynamics and that environmental investments, such as ecological restoration and reducing nutrient discharge, can significantly reduce CO2 emissions from inland lakes. This study provides valuable information on the reduction in carbon emissions from artificially controlled eutrophic lakes and an assessment of the impact of inland water on the global carbon cycle.

Urban warming advances spring phenology but reduces the response of phenology to temperature in the conterminous United States.

Urbanization has caused environmental changes, such as urban heat islands (UHIs), that affect terrestrial ecosystems. However, how and to what extent urbanization affects plant phenology remains relatively unexplored. Here, we investigated the changes in the satellite-derived start of season (SOS) and the covariation between SOS and temperature (RT ) in 85 large cities across the conterminous United States for the period 2001-2014. We found that 1) the SOS came significantly earlier (6.1 ± 6.3 d) in 74 cities and RT was significantly weaker (0.03 ± 0.07) in 43 cities when compared with their surrounding rural areas (P < 0.05); 2) the decreased magnitude in RT mainly occurred in cities in relatively cold regions with an annual mean temperature <17.3 °C (e.g., Minnesota, Michigan, and Pennsylvania); and 3) the magnitude of urban-rural difference in both SOS and RT was primarily correlated with the intensity of UHI. Simulations of two phenology models further suggested that more and faster heat accumulation contributed to the earlier SOS, while a decrease in required chilling led to a decline in RT magnitude in urban areas. These findings provide observational evidence of a reduced covariation between temperature and SOS in major US cities, implying the response of spring phenology to warming conditions in nonurban environments may decline in the warming future.

Stable Sulfur Isotopes Revealed a Major Role of Transition-Metal Ion-Catalyzed SO2 Oxidation in Haze Episodes.

Secondary sulfate aerosols played an important role in aerosol formation and aging processes, especially during haze episodes in China. Secondary sulfate was formed via atmospheric oxidation of SO2 by OH, O3, H2O2, and transition-metal-catalyzed (TMI) O2. However, the relative importance of these oxidants in haze episodes was strongly debated. Here, we use stable sulfur isotopes (δ34S) of sulfate aerosols and a Rayleigh distillation model to quantify the contributions of each oxidant during a haze episode in Nanjing, a megacity in China. The observed δ34S values of sulfate aerosols showed a negative correlation with sulfur oxidation ratios, which was attributed to the sulfur isotopic fractionations during the sulfate formation processes. Using the average fractionation factor calculated from our observations and zero-dimensional (0-D) atmospheric chemistry modeling estimations, we suggest that OH oxidation was trivial during the haze episode, while the TMI pathway contributed 49 ± 10% of the total sulfate production and O3/H2O2 oxidations accounted for the rest. Our results displayed good agreement with several atmospheric chemistry models that carry aqueous and heterogeneous TMI oxidation pathways, suggesting the role of the TMI pathway was significant during haze episodes.

The fertilization effect of global dimming on crop yields is not attributed to an improved light interception.

Global dimming, a decadal decrease in incident global radiation, is often accompanied with an increase in the diffuse radiation fraction, and, therefore, the impact of global dimming on crop production is hard to predict. A popular approach to quantify this impact is the statistical analysis of historical climate and crop data, or use of dynamic crop simulation modelling approach. Here, we show that statistical analysis of historical data did not provide plausible values for the effect of diffuse radiation versus direct radiation on rice or wheat yield. In contrast, our field experimental study of 3 years demonstrated a fertilization effect of increased diffuse radiation fraction, which partly offset yield losses caused by decreased global radiation, in both crops. The fertilization effect was not attributed to any improved canopy light interception but mainly to the increased radiation use efficiency (RUE). The increased RUE was explained not only by the saturating shape of photosynthetic light response curves but also by plant acclimation to dimming that gradually increased leaf nitrogen concentration. Crop harvest index slightly decreased under dimming, thereby discounting the fertilization effect on crop yields. These results challenge existing modelling paradigms, which assume that the fertilization effect on crop yields is mainly attributed to an improved light interception. Further studies on the physiological mechanism of plant acclimation are required to better quantify the global dimming impact on agroecosystem productivity under future climate change.

Eutrophic Lake Taihu as a significant CO2 source during 2000-2015.

Inland lakes receive growing attentions on eutrophication and their roles in global carbon cycle. However, understanding how inland lakes contribute to global carbon cycle is seriously hampered due to a shortage of long-term records. This study investigated the carbon dioxide (CO2) flux from the Lake Taihu, a large (2400 km2) and shallow (mean depth 1.9 m) eutrophic lake in subtropical region, based on a long-term (2000-2015) measurement of the partial pressure of carbon dioxide (pCO2) at high spatiotemporal resolution. We found that the Lake Taihu was a significant source of atmospheric CO2 with an average CO2 emission flux at 18.2 ± 8.4 mmol m-2 d-1 (mean±1standard deviation) and a mean annual pCO2 value of 778 ± 169 µatm. The highest pCO2 and CO2 flux were observed in eutrophic zone with a high external input of carbon and nutrient, and the lowest in non-eutrophic zones with no direct external input of nutrient and carbon. A substantial seasonal pattern in pCO2 was observed, particularly in eutrophic pelagic area, and was significantly negatively correlated with chlorophyll a. Long-term measurement showed the interannual variation in annual lake CO2 dynamics, which was highly sensitive to human-induced nutrient input. Watershed input of carbon and nutrient leads to the high CO2 level, counterbalancing the in-lake primary production. All lines of evidence suggest that human activities may have predominate contribution to CO2 source in the Lake Taihu, and this mechanism might be widespread in global freshwater lakes.

Surface nitrous oxide concentrations and fluxes from water bodies of the agricultural watershed in Eastern China.

Agriculture is one of major emission sources of nitrous oxide (N2O), an important greenhouse gas dominating stratospheric ozone destruction. However, indirect N2O emissions from agriculture watershed water surfaces are poorly understood. Here, surface-dissolved N2O concentration in water bodies of the agricultural watershed in Eastern China, one of the most intensive agricultural regions, was measured over a two-year period. Results showed that the dissolved N2O concentrations varied in samples taken from different water types, and the annual mean N2O concentrations for rivers, ponds, reservoir, and ditches were 30 ±â€¯18, 19 ±â€¯7, 16 ±â€¯5 and 58 ±â€¯69 nmol L-1, respectively. The N2O concentrations can be best predicted by the NO3--N concentrations in rivers and by the NH4+-N concentrations in ponds. Heavy precipitation induced hot moments of riverine N2O emissions were observed during farming season. Upstream waters are hot spots, in which the N2O production rates were two times greater than in non-hotspot locations. The modeled watershed indirect N2O emission rates were comparable to direct emission from fertilized soil. A rough estimate suggests that indirect N2O emissions yield approximately 4% of the total N2O emissions yield from N-fertilizer at the watershed scale. Separate emission factors (EF) established for rivers, ponds, and reservoir were 0.0013, 0.0020, and 0.0012, respectively, indicating that the IPCC (Inter-governmental Panel on Climate Change) default value of 0.0025 may overestimate the indirect N2O emission from surface water in eastern China. EF was inversely correlated with N loading, highlighting the potential constraints in the IPCC methodology for water with a high anthropogenic N input.

Methane flux dynamics in a submerged aquatic vegetation zone in a subtropical lake.

Submerged macrophytes are important primary producers for shallow lake systems. So far, their overall role in regulating lake methane flux is a subject of debate because the oxygen produced by their roots can promote methane oxidation in the sediment but they can also enhance methanogenesis through organic substrate production. In this study, we used the eddy covariance method to investigate the temporal dynamics of the CH4 flux in a habitat of submerged macrophytes in Lake Taihu. The results show that the nighttime CH4 flux is on average 33% higher than the daytime flux, although a clear diurnal pattern is evident only in the spring. At the daily to the seasonal time scale, the sediment temperature is the main driver of the CH4 flux variations, implying higher methane production in the sediment at higher temperatures. The annual CH4 emission (6.12 g C m-2 yr-1) is much higher than the published whole-lake mean flux (1.12 g C m-2 yr-1) and that reported previously in the eutrophic phytoplankton zone of the lake (1.35 g C m-2 yr-1), indicating that the net effect of the submerged macrophytes is to enhance methane emission. At the annual time scale, 3.5% of the carbon gained by the net ecosystem production is lost to the atmosphere in the form of CH4.